Evaluating recycling potential of demolition waste considering building structure types: A study in South Korea

Journal Pre-proof Evaluating recycling potential of demolition waste considering building structure types: A study in South Korea Gi-Wook Cha, Hyeun Jun Moon, Young-Chan Kim, Won-Hwa Hong, Gyu-Yeob Jeon, Young Ran Yoon, Changha Hwang, Jung-Ha Hwang PII:

S0959-6526(20)30432-7

DOI:

https://doi.org/10.1016/j.jclepro.2020.120385

Reference:

JCLP 120385

To appear in:

Journal of Cleaner Production

Received Date: 26 August 2018 Revised Date:

31 January 2020

Accepted Date: 1 February 2020

Please cite this article as: Cha G-W, Moon HJ, Kim Y-C, Hong W-H, Jeon G-Y, Yoon YR, Hwang C, Hwang J-H, Evaluating recycling potential of demolition waste considering building structure types: A study in South Korea, Journal of Cleaner Production (2020), doi: https://doi.org/10.1016/ j.jclepro.2020.120385. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

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Evaluating Recycling Potential of Demolition Waste Considering Building Structure

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Types: A study in South Korea

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Gi-Wook Cha a, Hyeun Jun Moon a*, Young-Chan Kim b, Won-Hwa Hong c, Gyu-Yeob Jeon d,

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Young Ran Yoon a, Changha Hwang e, Jung-Ha Hwang f

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a

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Yongin 16890, Korea

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b

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Hanyangdaehak‐ro, Sangnok‐gu, Ansan 426‐791, Korea

Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Suji-gu,

Innovative Durable Building and Infrastructure Research Center, Hanyang University, 55

10

c

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University, 80 Daehak-ro, Buk-gu, Daegu 41566, Korea

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d

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Jeju-si, Jeju Special Self-Governing Province 63243, Korea

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e

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16890, Korea

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f

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41566, Korea

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*

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Tel.: +82-31-8005-3733; Fax: +82-31-8021-7224

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School of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National

Department of Architectural Engineering, Jeju National University, 102 Jejudaehak-ro,

Department of Applied Statistics, Dankook University, 152 Jukjeon-ro, Suji-gu, Yongin

School of Architecture, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu

Corresponding Author, E-Mail: [email protected]

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Abstract

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This study investigates the recycling potential of demolition waste (DW) according

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to building structure, while considering environmental and economic aspects For that, this

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study surveyed 1,034 residential buildings in Korea immediately before demolition to collect

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reliable information on demolition waste generation rates (DWGRs). This study classified the

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removal stages of buildings into the demolition, collection and sorting, transportation, and

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disposal stages. This study suggested a method for carbon emissions calculation for each

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stage and carried out an inventory analysis. The economic value of recycled DW materials

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was also calculated. Furthermore, the recycling potential was calculated based on the

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economic value and the environmental load for the current scenario, i.e., the current waste

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recycling rate in Korea, and the maximum scenario, i.e., the maximum theoretical recycling

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rate. Regarding building structures, the recycling potential of wooden structures was the

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highest in both the scenarios. However, masonry-block structures showed improved recycling

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potential in the maximum scenario. Regarding DW types, the recycling potential of plastics

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was the highest, with plastics from reinforced concrete (RC) structures showing 6.6 times

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higher recycling potential than those from wooden structures. And the possibility of

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improving the recycling potential was higher for glass and plastics than aggregates, timber,

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and metals. Through the above research, this paper devised an approach that can be used to

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plan a detailed construction and demolition waste management strategy, considering building

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structures and DW types, and this method can also be applied to other regions and countries.

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Keywords: Demolition Waste; Waste Generation Rate; Building Structure; Recycling

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Potential; Environmental Effect; Economic Value

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1. Introduction

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Globally, construction and demolition (C&D) activities generate large amounts of waste

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(Llatas, 2011; Li et al., 2013; Wang et al., 2015). Demolition waste (DW) accounts for over

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70–90% of total C&D waste (Lu et al., 2011; Butera et al., 2014; U.S. EPA, 2016; Wang et al.,

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2018a). Additionally, lack of available land in urban areas necessitates demolition of existing

50

buildings before construction of new ones (Martínez et al., 2013). Therefore, governments

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and industry practitioners are making great efforts to reduce environmental burdens through

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proper management and recycling of demolition waste. Also, in this context, some

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researchers have conducted research on the recyclability of DW.

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Existing studies on DW recycling have considered environmental impact or economic values.

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Duran et al. (2006), Wu et al. (2016a), Wu et al. (2016b) and Yu et al. (2020) focused on the

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recycling value of DW from economic aspects. The researchers determined the recycling

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potential by using the recycling rate and economic benefits of the recycled products.

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Thormark (2001; 2002) and Blengini (2009) focused on the recycling potential of DW in

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terms of environmental aspects. Thormark (2001) focused on the conservation of energy and

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natural resources for recycling and landfilling. Blengini (2009) focused on energy and CO2

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emission-control efficiency during DW recycling. On the other hand, Klang et al. (2003)

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proposed a model for evaluating the environmental, economic, and social (including

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occupational health and working environment) aspects of the sustainable management of DW.

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Existing studies on the recycling potential of DW focus on environmental aspects (Thormark,

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2001, 2002; Blengini, 2009), economic aspects (Duran et al., 2006; Wu et al., 2016a; Yu et al.,

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2020), and a combination of these two aspects (Klang et al., 2003). These studies analyzed

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the categories of DW generated, but overlooked an important fact, namely, the effect of

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building structure types on the demolition process and DW generation characteristics. For

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example, reinforced concrete (RC) structures require a crusher in the building demolition

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process, whereas structures without RC require a bucket. In addition, the combination of

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equipment used differs at the sorting and secondary crushing stages (where large chunks need

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to be crushed even after the building’s demolition) depending on the building structure. In

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other words, the energy and cost invested in the DW generated at the end of building life

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cycle differ according to the building structure, so the DW recycling strategy account for the

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building structure. Differences in building structure types affect their construction techniques

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(Cochran et al., 2007), and these differences are reflected in the DW composition. In other

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words, structural characteristics of a building should be considered to more accurately

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calculate the amount of C&D waste. Therefore, a few studies on demolition waste generation

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rates (DWGRs) have considered building structure types for such analysis (Wu et al., 2016a;

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Cha et al., 2017; Cochran et al., 2007; Ding and Xiao, 2014). As described above, the

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structure of buildings greatly influences the DWGR, which can lead to more accurate and

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reliable estimation results. In addition, as mentioned before, the building structure type plays

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a vital role in the demolition process. Therefore, the information on DW should be collected

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by considering the building structure, and the DWGR data should be calculated on the basis

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of this information.

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An important challenge in understanding the recycling potential of DW generated at the end

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of life (EOL) phase is the need for data on the economic value and environmental load in the

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flow and process of the EOL phase of a building. In this context, this study should subdivide

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the process of the EOL phase of the building and collect data related to environmental and

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economic values based on subdivided EOL phase. Studies that have adopted the life cycle

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assessment (LCA) approach provide examples for understanding the flow and process of the

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EOL phase of a building (Wang et al., 2018b; Tae et al., 2011; Zhang and Wang, 2015;

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Coelho and de Brito, 2013a; Coelho and de Brito, 2013b; Peng, 2016). These researchers

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attempted to calculate CO2 emission accurately and reliably by collecting inventory data after

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classifying the EOL phase of a building in detail according to the characteristics of the

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demolition activities. Similarly, if data about economic activities is available, researchers

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could gain a deeper understanding about DW recycling from the recycling potential, which is

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obtained after considering the economic and environmental values of DW generated at the

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EOL phase of buildings.

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The objective of this study is to investigate the recycling potential of DW (i.e., waste from a

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building demolition process), which is generated at the end of the building lifecycle, by

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considering building structure types. In the present study, first, through actual field surveys,

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the amount of DW generated according to building structure types was investigated and

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analyzed. Then, reliable DWGRs according to building types were established through data

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preprocessing. Second, the end of the building life cycle was divided into four stages: (a)

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structure demolition, (b) collection and sorting, (c) transportation, and (d) treatment. Then, an

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inventory analysis for calculating CO2 emission and operational cost was conducted based on

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the used equipment and energy consumption. Third, the evaluation results on the recycling

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potential of DW according to building structure type (considering both environmental and

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economic aspects) were presented. Finally, the application of the study results were discussed.

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This study used operational cost and the sales price of recycled DW materials as an economic

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index and the CO2 emissions as an environmental index. The results will provide a tool for

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deciding how environmentally friendly and economical the DW recycled materials are.

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2. Methods and materials

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The framework of this study evaluates the recycling potential depending on the structure and

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DW type in the building EOL phase. As shown in Figure 1, this study provides DWGR,

118

inventory, and economic value data for each building structure and DW type. Based on this,

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the framework calculates the following according to the recycling scenario: 1) carbon

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emission, 2) economic value, and 3) recycling potential. Results 1) to 3) are provided at both

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the DWs and the buildings. Finally, based on these results, the recycling potential can be

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interpreted depending on the type of building and DW.

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Figure 1. Conceptual framework for calculating the recycling potential on the basis of DW

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and building structure type (RP is recycling potential)

126 127

2.1. Collecting DWGR data for building structure type

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2.1.1. Survey description and data collection method

129

The present study collected data on urban regeneration project districts in Daegu and Busan,

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which are large cities located in the southern part of Korea. The locations of the study areas

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were as follows: Project A in Daegu (35.88°N latitude, 128.61°E longitude), Project B in

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Busan (35.87°N latitude, 128.63°E longitude), and Project C in Busan (35.21°N latitude,

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129.04°E longitude). The reasons for choosing the study areas were as follows. 1) A case

134

study on urban regeneration project districts could provide useful information to the

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government and other waste management stakeholders. 2) The target area includes aged

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buildings slated for demolition and reconstruction. In this study, A preliminary survey of

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1,034 buildings in the study area to ensure reliable data collection was conducted. Table 1

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shows the status of the buildings for each project.

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Table 1. Characteristics of buildings in this study. Average floor area Structure type

Number of buildings

2

Total floor area (m ) (m2)

RC

147

56,929

387.3

Concrete-brick

170

21,783

128.1

Masonry-block

432

35,153

81.4

Wood

285

22,750

79.8

Total

1,034

136,615

-

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The main members and materials of the buildings (e.g., roof, walls, floor, ceiling, stairs,

142

windows, doors, and fence) were examined just before the building demolition process. In

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addition, building surveys were conducted by two persons, and data on structure types and

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major components were recorded. The material quantities of the major members were

145

investigated by measuring the length, height, thickness, and shape. The measured data were

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recorded on the data sheet, along with the plan drawn using AutoCAD. Then, the major

147

component quantities were calculated through squaring. Based on these quantities, the DW

148

was estimated and classified into 10 types: mortar, concrete, block, brick, timber, roofing tile,

149

plastics, metals, glass, and other waste. In addition, drawings and data on general

150

characteristics of the buildings (area, address, use, structure, wall material, roof material,

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floor area, number of floors, etc.) were collected. Figure 2 shows the building survey process

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of one of the buildings.

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Figure 2. Surveying each building part: A (survey of building structure and general

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characteristics), B (wall), C (roof), D (window frame), E (door), F (indoor ceiling and floor),

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and G (stairs)

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2.1.2. Demolition waste generation rates for different building structure types

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This study collected data by considering the different structure types shown in Table 1.

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Furthermore, based on the collected data, the DWGR was calculated using Eq. (1), in which

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the type of building and the properties of the DW were considered:

161







∑

=













(1)

162

is the amount of material j with properties of waste material i (quantity) (m3, or

163

where

164

m2, or ton) and GFA is the gross floor area (m2).

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In this study, data about 10 types of DWs were collected from 1,034 buildings. These data

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were preprocessed to ensure the reliability and quality of the data. For data preprocessing,

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data in the range of 1Q (Quartile)-1.5 * IQR (Inter Quartile Range) < selecting data < 3Q +

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1.5 * IQR (where Q denotes Quartile and IQR equals Q3−Q1) were extracted according to

169

the building structure and waste type, and the averages were used as DWGRs. Figures S1–S4

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show the range of selecting data after preprocessing for each building type as a box plot. And

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then, statistical analysis was performed to confirm whether the types of DWs and the amount

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of DWs differ depending on the structure of the building. First, the normality test for the

173

amount of DWs, which is a dependent variable, was performed for the entire data set and the

174

IQR data set, respectively. The results showed that both the entire dataset before data

175

preprocessing and the IQR dataset do not follow a normal distribution. Therefore, in this

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study, ANOVA analysis was performed through the Kruskal Wallis test, a non-parametric

177

method, to verify the difference between the feature (i.e., building structures) and the

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dependent variable (i.e., amount of DWs) (see the Figure S5, S6). As a result of the Kruskal

179

Wallis test, p-value <0.5 in both total dataset and IQR dataset showed that the amount by DW

180

type was different depending on the structure (see the Table S1). Through the above ANOVA

181

analysis, the amount by DW types collected in this study clearly shows the difference

182

depending on the structure. Therefore, the recycling potential of DWs supports the

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assumption of this study that it is appropriate to consider the effect of structure.

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Table 2 show the results and distribution ratios of the DWGRs according to building structure

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type after data preprocessing. As shown in Table 2, the DWGRs and their distribution ratios

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vary greatly depending on the building structure type. Total DWGR is the highest for RC

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structures (1,676.4 kg/m2) and lowest for wooden structures (911.5 kg/m2). In particular, the

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DWGRs in terms of volume per unit area of the wooden and masonry-block structures are

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0.855 and 0.999 m3/m2, respectively. This is considerably lower compared to the DWGRs in

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terms of volume per unit area (911.5 and 1,135.5 kg/m2) (Table 2). This may be attributed to

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the DW composition of wooden structures. In terms of DW composition according to

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building structure type, mineral waste, such as mortar, concrete, brick, and block, occupies

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more than 93% of DW in RC and concrete-brick structures. On the other hand, masonry-

194

block (81%) and wood (72%) structures showed a low proportion of mineral waste. Thus, the

195

DWGRs and distribution ratios differed greatly depending on the type of building structure.

196

These differences significantly affect CO2 emissions generated from each life cycle stage

197

(e.g., building demolition, collection and sorting, transportation, and disposal) and the

198

economic value of the recycled DW products. Therefore, the data collected in this study are

199

suitable for research on recycling potential according to building structure type.

200

Table 2. DWGRs by building type and structure in terms of m3/m2 and kg/m2. Building structure Waste type

Reinforced Concrete-brick

Masonry-block

Wood

concrete (RC) Mortar

0.017 (34.2)

0.058 (115.7)

0.052 (103.2)

0.096 (191.4)

Concrete

0.239 (549.0)

0.167 (384.3)

0.063 (146.0)

0.019 (43.3)

Block

0.304 (577.8)

0.036 (69.3)

0.344 (654.4)

0.120 (227.7)

Brick

0.205 (409.0)

0.403 (806.8)

0.009 (17.2)

0.097 (193.9)

Timber

0.037 (22.1)

0.130 (76.6)

0.210 (123.7)

0.163 (96.4)

Roofing tile

0.011 (2.1)

0.227 (44.9)

0.299 (59.2)

0.301 (59.6)

Plastics

0.029 (34.9)

0.015 (18.2)

0.018 (21.9)

0.004 (5.2)

Metals

0.005 (38.1)

0.002 (14.0)

0.0004 (3.1)

0.0002 (1.5)

Glass

0.003 (5.8)

0.003 (6.6)

0.002 (3.7)

0.002 (5.0)

Other waste

0.002 (3.4)

0.001 (1.7)

0.002 (3.1)

0.053 (84.0)

Total

0.851 (1,676.4)

1.042 (1,538.1)

0.999 (1,135.5)

0.855 (911.5)

201

* Numbers outside (inside) the parentheses are in m3/m2 (kg/m2).

202

203

2.2. Calculation of carbon emission and operational cost in the EOL phase of buildings

204

The EOL phase of a building can be classified into four stages: building demolition,

205

collection and sorting, transportation, and disposal (Wu et al., 2016a, 2016b, Wang et al.,

206

2018). Accordingly, the EOL phase was classified into four sub-stages in this study, and the

207

activities of each stage were as follows. Building demolition produces DW. During the

208

collecting and sorting stage, the waste is classified into four groups: (1) masonry materials

209

waste (e.g., concrete, brick, block, roofing tiles, and mortar), (2) non-combustible waste (e.g.,

210

metal and glass), (3) combustible waste (e.g., timber and plastic), and (4) mixed fragments.

211

The transportation stage involves loading the DW onto vehicles and transporting it to

212

recycling facilities. Lastly, the disposal stage involves recycling, incinerating, and landfilling

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DW according to its type and physical characteristics. Therefore, CO2 emissions and

214

operational cost for the Life Cycle DW can be calculated as the sum of CO2 emissions and

215

operational cost produced during each life cycle stage, as shown in Eq. (2). Furthermore, the

216

carbon emissions calculations for each stage are shown in Sections 2.2.1–2.2.4.

217

218 219

.

!"

where .

%& ,

= ∑( . .

!"

.

() ,

%&

+ .

+ .

()

*

+ .

%)

(2)

refers to the CO2 emissions generated at the end of the building life, and .

* , and

.

%

denote the CO2 emissions generated at the demolition stage,

220

collection and sorting stage, transportation stage, and disposal stage, respectively. Equation (2)

221

can also be applied to calculate the operational cost.

222

2.2.1. Demolition stage

223

At the demolition stage, CO2 emission and operational cost considering the building structure

224

type can be calculated by considering the expected amount of waste generated (or workload

225

of the demolition equipment), energy consumption and work efficiency of equipment

226

combinations, and CO2 emission factors of energy used by the equipment. Therefore, CO2

227

emissions at the demolition stage are calculated using Eq. (3). The operational cost is

228

calculated by Eq. (4). = ∑[(. ∗

229

.

230

6

231

where

232

($/m2) from the demolition stage, . is the amount of waste generated (m3/m2) by the

233

demolition equipment and equipment combination i,

234

the demolition equipment i, 01 is the carbon emission coefficient (kg CO2/ L) of unit energy

235

used by i; and 34 is the work efficiency per hour (m3/h) of i.

236

the equipment combination i.

237

2.2.2. Collection and sorting stage

238

The materials inside the building show a sponge effect after the demolition process, and this

239

effect should be considered for each life cycle stage (Llatas, 2011; Cheng and Ma, 2013).

240

Therefore, CO2 emissions and operational cost at the collection and sorting stage can be

241

calculated using Eqs. (5) and (6), respectively, which consider the volume change rate (Llatas,

242

2011) by DW type, as well as the energy consumed by equipment combinations and general

243

CO2 emissions factors.

244

.

%

%

()

= ∑[(. ∗ .

%

∗ 01 )/34 ]

(3)

)/34 ],

(4)

%&7

and 6

%

= ∑[(9:7 ∗ . ∗

denote the CO2 emissions (kg CO2-eq/m2) and operational cost

∗ 01 )/34 ]

is the energy consumed (L/h) by

%&7

is hourly cost ($/h) of

(5)

= ∑[(9:7 ∗ . ∗

245

6

246

where

247

($/m2) from the collection and sorting stage, respectively. .

248

j by equipment i,

249

carbon emissions coefficient (kg CO2/ L) of unit energy used by demolition equipment i, 34

250

is the work efficiency per hour (m3/h) of demolition equipment i, and 9:7 is the volume

251

increase rate of waste j.

252

sorting waste j.

253

Crawler excavators are usually used during the collection and sorting stage. However,

254

separating reinforcing bars from concrete in RC structures is difficult with a crawler

255

excavator. Accordingly, the separation work requires equipment, such as rotating hydraulic

256

breakers. Therefore, this study considers combinations of such equipment (see Section 2.3).

257

2.2.3. Transportation stage

258

CO2 emissions and operational cost are produced by vehicles at the transportation stage. Thus,

259

the types of vehicles, distance, transportation time, and number of vehicles must be taken into

260

consideration for energy consumption calculations. Furthermore, the fuel efficiency of

261

transportation vehicles differs depending on whether the vehicle is empty or loaded with DW.

262

The volume change rate of DW must also be considered during the transportation stage.

263

Therefore, CO2 emissions and operational cost at the transportation stage are calculated using

264

Eqs. (7) and (8), respectively.

265

.

266

6

()

*

*

.

()

and 6

()

;<7

)/34 ]

(6)

refer to the CO2 emissions (kg CO2-eq/m2) and operational cost is workload (m3/m2) of waste

is the energy consumed (L/h) by demolition equipment i, 01 is the

;<7

is the hourly cost ($/h) of equipment i used for collecting and

= ∑[9:7 ∗ . ∗ 01 ∗ => /(14?7 ∗ 9@7 )]

= ∑[9:7 ∗ . ∗ => ∗

* /(AB

∗ 9@7 )

(7) (8)

.

and 6

refer to CO2 emissions (unit: kg CO2-eq/m2) and operational cost

267

where

268

($/m2) from the transportation stage, respectively. .

269

transported by vehicle i; 01 is the carbon emission coefficient (kg CO2-eq/L) of unit energy

270

used by transportation vehicle i; => is the transportation distance; 14?7 is the fuel

271

efficiency (km/L) of transportation vehicle i; 9:7 is the volume increase rate of waste j; and

272

9@7 is the load (m3) of transportation vehicle i.

273

vehicle ($/h)., and AB is the hourly transportation distance of the transportation vehicle; here,

274

AB was chosen to be 40 km/h considering waste loading and unloading and the transportation

275

time.

276

2.2.4. Disposal stage

277

At the disposal stage, the waste disposal method varies depending on the physical

278

characteristics. Carbon emissions and disposal cost can be calculated using the amount of

279

waste disposed and carbon emission factors and disposal cost according to the waste disposal

280

method (e.g., recycling, incineration, and landfilling). Therefore, CO2 emissions and disposal

281

cost from the disposal stage can be calculated using Eqs. (9) and (10).

*

*

*

is amount (unit: m3/m2) of waste j

is the hourly cost of transportation

= ∑(. ∗ 01 )

282

.

283

6

284

where

285

($/m2) at the disposal stage, respectively. . is the recycled amount (unit: kg/m2) of waste i,

286

and 01 is the carbon emissions factor (kg CO2-eq/kg) according to the disposal method used

287

for waste i.

288

2.3. Inventory analysis

%

%

= ∑(. ∗ .

%

%7

and 6

%7

(9) )

(10)

%

refer to the CO2 emissions (unit: kg CO2-eq/m2) and disposal cost

is the disposal cost of waste type i ($/ton)

289

This section provides the results of the inventory analysis for each life cycle stage of DW.

290

The results from this section were applied to the equations presented in Section 2.2 to

291

estimate the CO2 emissions produced. In addition, this section provides operational cost

292

information, including material and labor cost and public expenditures at each stage.

293

2.3.1. Demolition stage

294

In this study, a combination of equipment actually used in the target area was investigated

295

according to building structure type. Based on these results, an inventory analysis of

296

operational cost, including material and labor cost, public expenditures, equipment type,

297

work efficiency, energy type, and energy consumption rate, was performed at the demolition

298

stage. Table 3 shows the inventory analysis results from the demolition stage in the target area.

299

Table 3. Work efficiency and energy consumption rates and operational cost of machines

300

used during the demolition stage. Work

Energy

Machine

Operational

Structure

efficiency

consumption

combination

cost ($/h) 3

(m /h)

rate (L/h)

11.8

19.6

88.6

76.4

17.7

75.7

11.8

19.6

88.6

Crawler excavator (1.0 m3)

76.4

17.7

75.7

Crawler excavator (1.0 m3)

76.4

17.7

75.7

Crawler excavator (1.0 m3) RC 3

+ hydraulic breaker (1.0 m ) Crawler excavator BrickCrawler excavator (1.0 m3) concrete 3

+ hydraulic breaker (1.0 m ) Masonry -block Wood 301

Note: Diesel was used as the fuel for all equipment.

302

2.3.2. Collection and sorting stage

303

A crawler excavator is typically used for collecting and sorting DW, but additional equipment

304

may be required. For example, an RC member requires the use of equipment, such as a

305

rotating hydraulic breaker, to separate the concrete and steel reinforcement after demolition.

306

Table 4 shows the inventory analysis results of the collection and sorting stage in the target

307

area.

308

Table 4. Work efficiency and energy consumption rates and operational cost of machines

309

used at the collection and sorting stage. Materials

Work

Energy Operational

collected and

Machine

efficiency

consumption cost ($/h)

3

sorted

(m /h)

rate

27.5

17.7

75.7

27.5

17.7

75.7

11.8

16.87

88.6

52.08

17.7

75.7

Crawler excavator Concrete 3

(1.0 m ) Crawler excavator Brick and block (1.0 m3) Rotating hydraulic Steel breaker Crawler excavator Others (1.0 m3) 310

Note: The type of fuel used is diesel. The energy consumption rate for the crawler excavator

311

and rotating hydraulic breaker is L/h and L/ton, respectively.

312

2.3.3. Transportation stage

313

Data on vehicle loading, mileage (in terms of empty and load), energy type, and

314

transportation distance are required for this stage. The loading according to vehicle size was

315

collected from the 2013 Korean standard pertaining to construction estimates (Korean

316

standard, 2013). Vehicle mileage, energy type, and transportation distance data were collected

317

from telephone interviews with companies using vehicles in the target area. These data were

318

reflected in the inventory in terms of the average value of 15 companies over one year.

319

According to the survey results, 15-t and 24-t trucks were used with diesel fuel, and the

320

average (one-way) transportation distance was 30.25 km (Table 5).

321

Table 5. Transportation distance and energy consumption rate and operational cost by vehicle

322

type.

Vehicle

Load size

Mileage (km/L)

Operational

(m3)

Load

Empty

($/h)

2

3

86.4

3

4.5

67.8

cost

Work

Transporting

mineral

waste (concrete, brick, 24-t

block, mortar, roofing 14.6 tiles)

to

treatment

facilities Transporting waste

(steel,

other timber,

15-t

9.13 plastics) to treatment facilities

323

Note: Diesel was used as the fuel and the round-trip distance was 60.5 km.

324

2.3.4. Disposal stage

325

The disposal stage involves recycling, incinerating, and/or landfilling of DW, all of which

326

were considering in this study according to the type of waste. DW recycling was limited to

327

recycling facilities. The CO2 emission factors according to the DW recycling method were

328

extracted from the life cycle inventory database provided by the Korea Environmental

329

Industry & Technology Institute (KEITI). For the disposal cost, the disposal rates of

330

intermediate and final recycling of companies notified by the Ministry of Environment (2017)

331

were used. Table 6 shows the CO2 emission factors and disposal cost according to the DW

332

recycling method at the disposal stage.

333

334

Table 6. CO2 emission factors and disposal cost for recycling DW. Disposal

Carbon emission DW type

methods

Disposal cost ($/ton) factor (kg CO2-eq/kg)

Mineral waste (concrete, brick, 1.38×10-2

33.4

Metal

3.80×10-3

199.1

Glass

9.78×10-3

33.9

Timber

1.36×10-2

40.2

Plastics

1.86×10-2

43.8

Glass

7.03×10-3

78.6

Timber

1.17×10-2

block, mortar, roofing tile) Recycling

Landfill

Incineration

190.2 Plastics

2.35

335

CO2 emission source: Korea Environmental Industry & Technology Institute (KEITI); Cost

336

source: Ministry of Environment, waste disposal prices by type for calculation of neglected

337

waste disposal deposit, 2017. However, for metals, the average purchase price for processed

338

iron

339

(http://www.index.go.kr/potal/main/EachDtlPageDetail.do?idx_cd=1143) was used instead of

340

the disposal cost.

341

2.4. Calculation model for recycling potential by DW and building structure type

342

The main purpose of this study is to evaluate the recycling potential, considering both

343

economic and environmental aspects according to building structure type when DW is

344

recycled. Therefore, the concept of recycling potential according to building structure type is

345

expressed as Eq. (11).

346

CDE@7 = ∑(. × GCH ) − 6

347

where CDE@7 is the recycling potential of building j, .

348

by demolishing building j, GCH

349

6

350

total emissions of building j.

351

The emissions trading price was considered to be 20.26$/ton-CO2, which is the 2018 average

352

trading

353

(http://marketdata.krx.co.kr/mdi#document=070301). And the value indices of recycled DW

354

products sourced from KORAS (https://www.koras.org/05/sale.jsp) and the Korea

355

Environment Corporation were used as the PRMs of the different DWs.

356

To calculate the recycling potential for each type of DW, it is necessary to understand the

357

flow of CO2 emissions of the DW in terms of the energy consumption during each life cycle.

358

However, currently, there is no way to estimate the energy input for each DW type at the

scraps

during

−

according

(11)

!"7

is the amount of waste i generated

is the market price of the recycled material for waste i,

is the total operational cost and

price

.

2015–2017

to

.

the

!"7

refers to emissions trading price for the

Korea

Exchange’s

market

data

359

demolition stage. Therefore, this study assumed that the CO2 emissions of a specific waste at

360

the demolition stage were distributed according to the ratio of specific waste generated by the

361

building. Thus, the CO2 emission flow for each waste type generated at the demolition stage

362

was calculated using Eq. (12). This equation can also be used to calculate the waste cost at

363

the demolition stage. .

364

= .

% 7

.

% 7

×I

(12)

365

where

366

j,

367

ratio of waste i in building j (%).

368

Therefore, using Eqs. (11) and (12), the recycling potential can be calculated for each DW

369

according to the building type using Eq. (13).

370

CJ3DE@7 = . × GCH − K6

.

% 7

% 7

refers to the CO2 emissions from waste i at the demolition stage of building

denotes the CO2 emissions of building j at the demolition stage, and I

% 7

+ 6

(()L*L%)

M−(

.

% 7

+

.

is the

(()L*L%)

371

)

(13)

372

C6.DE@7

373

generated by building j, GCH is the market price of the recycled material i,

374

6

375

stage of building j, respectively.

376

trading price by the CO2 emissions and operational cost of waste i at the collection and

377

sorting, transportation, and disposal stages of building j, respectively. It is important to

378

include the final element in Eq. (13), as CO2 emissions and operational cost generated during

379

all the stages mentioned herein must be considered when calculating CJ3DE@7 .

380

2.5. Recycling rate scenarios for demolition waste

% 7

is the recycling potential of waste i in building j, .

is the amount of waste i .

% 7

and

denotes the CO2 emissions and operational cost due to waste i at the demolition .

(()L*L%)

and 6

(()L*L%)

refer to emissions

381

To compare the recycling potential of DW, this study considers two scenarios: the current

382

scenario (reflecting the current status of waste disposal in Korea) and the maximum scenario

383

(the maximum theoretical recycling rate by waste type).

384

In the current situation in Korea, more than 99% of the mineral waste group (concrete, mortar,

385

block, brick, and roofing tiles) is being recycled. The mineral waste group is mainly used as

386

aggregate for building road sub-bases, an application that does not require superior quality

387

materials. Therefore, mineral wastes in DW show a very high recycling rate in Korea. In

388

addition, timber and metal have a high recycling rate due to the high sales value of the

389

recycled products in related industries. In the case of metal, the recycling rate is zero based

390

on the information provided by the national waste disposal statistics. This is because metals

391

are sold to relevant recycling companies as soon as they are collected on site due to their high

392

recycling value. Therefore, this study assumed that the recycling rate of metal was 100%. On

393

the other hand, recycling rates for plastics and glass are as low as 52% and 14%, respectively.

394

In this study, the maximum recycling rates of DW are assumed to be 95%. Theoretically, the

395

majority of DW can be recycled at the rate of 95% except for insulation materials and mixed

396

fragments (Wu et al., 2016b). For DW that is currently recycled at a rate of 95% or more in

397

Korea, the maximum recycling rate is assumed to be equal to the current recycling rate. In the

398

maximum recycling rate scenario, the recycling rates of the mineral waste group, metal, and

399

timber are equal to the recycling rates in the current situation because there was no possibility

400

to increase their recycling rates. The maximum recycling rates for plastics and glass were

401

assumed to be 95%, per the applicable convention (Wu et al., 2016b). Incineration and

402

landfilling can be considered as treatment methods other than recycling for plastics and glass,

403

respectively. Table 7 compares the two above-mentioned scenarios for DW recycling rates

404

using the available national statistics on DW treatment.

405

406

Table 7. Disposal scenarios pertaining to DW in this study. Current

Maximum

recycling rate

recycling rate

Waste type

Incineration Landfill rate rate

Concrete Mortar

99.9%

Block

100%

Brick

99.38%

Mineral

Same as

waste

current

group

-

-

-

-

situation Roofing 99.29% tile Same as

Metal

100%

current situation Same as

1 minus Timber

94.82%

current

recycling rate

situation 1 minus Plastics

52.01%

95%

recycling rate 1 minus

Glass/ceramic

14.02%

95%

recycling rate

Mixed waste 407

408

3. Results and discussion

409

3.1. Analysis of carbon emissions and operational cost by building structure

410

Table 8 show the results of CO2 emissions (kg CO2-eq/m2) according to building structure

411

and DW type in the EOL phase of buildings in this study. Table S2 show the results of

412

operational cost ($/m2) according to the building structure and DW type in the EOL phase of

413

buildings. In Table 8, CO2 emissions show different results depending on building structure

414

and DW type. This is the reason that the main structural materials of the buildings are

415

different. For this reason, RC and concrete-brick structures show relatively high CO2

416

emissions in some DW, such as concrete, block, and brick. On the other hand, masonry-block

417

and wood structures have relatively high CO2 emissions in DW, such as mortar and block.

418

The CO2 emissions of aggregates (e.g., mortar, concrete, block, brick, roofing tile) are due to

419

different types of equipment used depending on the building structure at the demolition stage.

420

Similarly, as shown in Table S2, the cost of building materials such as concrete, blocks, and

421

bricks make up a large part of the operational cost, and the DW type of major structural

422

materials shows a high operational cost result. Furthermore, metals occupy a relatively high

423

share of the operational cost compared with CO2 emission. On the other hand, plastic has the

424

highest CO2 emission results (Table 8). This is because plastic contributes a large amount of

425

CO2 emission from the disposal stage, unlike the aggregate with high CO2 emission generated

426

from equipment used at the disposal stage. According to the recycling scenario in this study,

427

the potential for CO2 emission reduction is low for aggregates, while plastic is fairly high.

428

Furthermore, the operational cost result (Table S2) shows a considerable cost reduction effect

429

on recycled plastics.

430

Looking at the results of CO2 emissions by structure type in the EOL phase of buildings, in

431

the former, CO2 emissions in the EOL phase were highest for RC structures (71.6 kg CO2-

432

eq/m2) and lowest for wooden structures (21.3 kg CO2-eq/m2). For the maximum recycling

433

rate scenario, CO2 emissions were the highest for RC structures (36.7 kg CO2-eq/m2) and

434

lowest for wooden structures (16.1 kg CO2-eq/m2). The CO2 reduction rates according to

435

building structure were 48.7% for RC, 38% for concrete-brick, 48.1% for masonry-block, and

436

24.4% for wooden structures. The highest CO2 reduction rate for the RC structures and

437

masonry-block may be attributed to the effect of avoiding incineration as a result of the

438

increased plastic recycling rate. On the other hand, as shown in Table S2, the operational cost

439

in the current scenario is the highest for RC structures (87.4 $/m2) and the lowest for wooden

440

structures (42.4 $/m2). However, in the maximum scenario, their operational cost reduction

441

rates are not large compared with those of CO2 emissions. The operational cost reduction

442

rates according to building structure were 2.75% for RC, 1.83% for concrete-brick, 2.63% for

443

masonry-block, and 1.2% for wooden structures. The reduction in operational cost is due to

444

the cost reduction effect from recycling of glasses and plastics instead of landfill and

445

incineration.

446

These results indicate that the flow of CO2 emission and operational cost differ by building

447

structure and material. Furthermore, as shown in Table 2, DWGRs values differ by building

448

structure. Therefore, the composition of DW from a building is considered to influence the

449

possibility of CO2 emissions and operational cost reduction in the EOL phase.

450

Table 8. Carbon emission by building structural and DW types according to the scenarios in this study. Recycling scenario

Structural type

CO2 emission(kgCO2-eq/m2)by DW type in this study Aggregates

Current recycling rate

Maximum recycling rate

451 452 453 454

Timber

Mortar

Concrete

Block

Brick

RC

0.65

10.43

11.33

Concretebrick

2.01

6.61

Masonryblock

1.78

Wood

Plastic

Metal

recycling

incineration

recycling

incineration

8.14

Roofing tile 0.10

0.54

0.19

0.53

39.55

1.23

14.61

2.03

1.75

0.67

0.26

2.49

11.58

0.31

2.67

2.81

1.08

3.29

0.74

4.02

3.48

2.68

2.18

RC

0.69

10.43

11.33

8.14

0.10

Concretebrick

2.01

6.61

1.23

14.61

Masonryblock

1.74

2.49

11.58

Wood

3.39

0.74

4.02

Glass

Total

recycling

landfill

2.07

0.02

0.06

71.6

20.61

0.74

0.02

0.06

48.1

0.31

24.79

0.16

0.02

0.03

45.5

0.84

0.07

5.89

0.09

0.02

0.04

21.3

0.54

0.19

0.85

4.24

2.07

0.13

0.08

36.7

2.03

1.75

0.67

0.41

2.21

0.74

0.08

0.08

29.8

0.31

2.67

2.81

1.08

0.49

2.66

0.16

0.05

0.05

23.6

3.48

2.68

2.18

0.84

0.12

0.63

0.09

0.06

0.06

16.1

455 456

457

3.2. Recycling potential by building type and demolition waste

458

As shown in Figure 3, for the current recycling rate, the recycling potential considering both

459

environmental (i.e., CO2 emissions) and economic aspects (i.e., price of recycled products

460

and operational cost) clearly differs depending on the building structure and waste type. First,

461

the recycling potential was highest for plastics and lowest for aggregates (e.g., concrete,

462

mortar, brick, block, and roofing tiles). Plastics have a high recycling potential because the

463

selling prices of recycled products are considerably higher than the operational cost and CO2

464

emission cost incurred for CO2 emission. By contrast, the recycling potential of aggregates is

465

much lower at -71 to -32 ($/m2). This is because most of the aggregate recycling products are

466

produced and sold at low prices. Therefore, considering the current recycling rate and the

467

operational cost at the disposal stage, high-value-added recycled products need to be

468

produced to increase the recycling potential of aggregates. The recycling potentials of wastes

469

other than aggregates (timber, plastics, metals, and glass) show an economic profit greater

470

than zero in both current and maximum scenarios. This result is much different from those

471

reported in the literature (Wu et al., 2016a; Wu et al., 2016b). For example, Wu et al. (2016a)

472

showed that the recycling potential of metals accounted for 66% of the total DW. Wu et al.

473

(2016a, 2016b)found that the recycling potential of metals was 64%, higher than that of other

474

waste. However, the previous two studies focused only on economic value without

475

environmental load and operational cost.

476

The recycling potential result of each waste type in this study is different from those reported

477

in the literature because this study considers both operational cost and environmental load. In

478

the present study, plastics had the highest recycling potential, and the recycling potentials of

479

metals, glasses, and timbers were greater than zero. By contrast, the recycling potential of

480

aggregates was less than zero in every structure, which is much lower than those of other

481

wastes. Considering the current treatment technologies and economic value of DW in Korea,

482

the possibility of improving the recycling potential was higher for glass and plastics than

483

aggregates, timber, and metals. This is because products made from recycled glass and

484

plastics are high-value-added products that their sales values exceed economic losses by

485

operational costs and environmental loads.

486

The recycling potential differed depending on structure, as well as type of waste (Figures 3

487

and 4). The recycling potential of aggregates was generally low, but it was the lowest for RC

488

structures (-70.7) and highest for wooded structures (-31.5). The recycling potential of

489

plastics was highest for RC structures (5.15) and lowest for wooden structures (0.78).

490

Similarly, the recycling potential of different types of waste, such as timber, metals, and glass,

491

varied depending on the structure. This result may be attributed to the variation in operational

492

cost and CO2 emissions due to differences in demolition equipment, demolition technology,

493

waste transportation equipment, and treatment technology. Therefore, the recycling potential

494

is considered to be affected by building structures even if the generated DWs are the same.

495

These results are expected to be useful in deriving the best environmental and economic

496

benefits in future DW management strategies.

497

In Figure 3 and Figure 4, the recycling potential at the maximum recycling rate did not show

498

any difference with regard to several DWs, such as aggregate, timber, and metals. This means

499

that the recycling rates of aggregates, timber, and metals in the current situation are not likely

500

to increase. In the future, however, operational cost and CO2 emission reductions resulting

501

from improvement in building demolition and treatment technologies, increased mileage of

502

transportation vehicles, and increased sales value of recycled products may improve the

503

recycling potential of aggregates, timber, and metals. Conversely, the recycling potential of

504

plastics and glass showed interesting results. In the current situation, the recycling potential

505

of plastics was about 5.15, 2.71, 3.27, and 0.78 for RC, concrete-brick, masonry-block, and

506

wooden structures, respectively, but the corresponding values for the maximum recycling

507

rates were 9.41, 4.95, 5.97, and 1.42, respectively, which are considerably higher compared to

508

the existing values. Furthermore, the recycling potential of glass in the maximum recycling

509

scenario was significantly higher (e.g., RC: 0.84, concrete-brick: 0.98, masonry-block: 0.55,

510

wood: 0.75) than that in the current situation (e.g., RC: 0.12, concrete-brick: 0.14, masonry-

511

block: 0.08, wood: 0.11). In this study, the change in DW recycling potential in the current

512

and maximum recycling rate situations was inconsistent with the result from a previous study

513

(Wu et al., 2016b), which showed that the recycling value of aggregates (e.g., concrete, brick,

514

block, and mortar) was most likely to improve. As shown in Table 9, This was because the

515

recycling rate situation only considered the recycling potential of DW from an economic or

516

environmental point of view. In other words, previous studies presented the same recycling

517

potential for the same DW. Thus, these studies did not consider the influence of the type or

518

structure of individual buildings. This study considered structural factors, which had not been

519

considered in previous works, and accordingly presented the DW recycling potential.

520 521 522

Figure 3. Recycling potential value by DW type according to the scenarios considered in this study (CS: current scenario; MS: maximum scenario)

523 524 525

Figure 4. Recycling potential by DW and structural types according to the scenarios considered in this study (CS: current scenario; MS: maximum scenario)

526

527

In the current situation, the recycling potential of DW differed depending on the structure of

528

the building (Figure 5). The recycling potential of DW was -68.9, -60.3, -39.6, and -29.9 for

529

RC, concrete-brick, masonry-block, and wooden structures, respectively. Thus, in the current

530

situation, wooden structural buildings showed the highest recycling potential, and RC

531

structures, the lowest. In other words, economic benefit relative to operational cost and CO2

532

emissions was the highest when the DW of wooden structural buildings was recycled,

533

whereas that for RC structures was the lowest. In the maximum scenario, the recycling

534

potentials were -59.7, -54.5, -34.2, and -27.7 for the RC, concrete-brick, masonry-block, and

535

wooden structures, respectively. Similarly, the recycling potential was the highest in wood

536

and the lowest in RC buildings. But the recycling potential increase rate was 13.3%, 9.1%,

537

14.5%, and 7.3% for RC, concrete-brick, masonry-block, and wood structures, respectively

538

(Figure 5). Thus, the increase rate of the recycling potential was the highest for masonry-

539

block and the lowest for wood buildings. In other words, as the recycling rate increased,

540

masonry-block structures showed the highest economic benefit relative to operational cost

541

and CO2 emissions, and wood buildings, the lowest. These results show that recycling

542

potential differed depending on the structure and type of waste, as shown in previous studies

543

(Blengini, 2009; Wu et al., 2016a; Cochran et al., 2007). Therefore, appropriate DW

544

management strategies according to the type of waste are required in the EOL phase, but the

545

environmental load and economic benefit will differ depending on the building type. Table 9

546

shows the characteristics and differences between previous research and this study on the

547

recycling potential of DWs generated at the EOL phase of buildings.

548

549

Figure 5. Possible improvement of recycling potential by building structure according to the

550

scenarios considered in this study

551

Table 9. Comparison of recycling potential results between existing research and this study. Reference

Country

Characteristics of recycling potential results Environmental Economic aspect Results by aspect structure type CO2 Using the prices RC of recycled Concrete-brick materials and Masonry-block operational cost Wood

This study

Korea

Blengini, 2009 Wu et al., 2016a

Italy China

GWP, GER, EI99 -

Wu et al., 2016b

China

Zheng et al., 2017

Yu et al., 2020

-

No

Using the prices of recycled materials

No

-

Using the prices of recycled materials

No

China

-

Using the prices of recycled materials

No

China

-

Using the prices of recycled materials

No

Results by waste type Aggregate (mortar, concrete, brick, block, roofing tile) Timber Plastics Metals Glass Aggregate Steel Aggregate (concrete, brick/block, mortar) Timber Copper Steer Aluminum Ceramic Glass Aggregate (mortar, concrete, brick) Metal Glass Others Aggregate (mortar, concrete, brick/block) Timber Metal Ceramic Aggregate (mortar, concrete, brick/block) Timber Metal Ceramic Steel Aluminum Copper Plastic

552

Note: GWP (Global warming potential), GER (Gross energy requirement), EI-99 (Eco

553

indicator-99)

554

In the present study, the recycling potential of aggregates, timber, and metals did not indicate

555

improvement for the current recycling situation in Korea because the recycling rates for the

556

DWs were already considerably high. However, it may be possible to improve the recycling

557

potential of these DWs if the sales values of the products recycled from these DWs are likely

558

to increase. In the current situation in Korea, recycling of glass and plastics can maximize

559

CO2 emissions reduction and economic benefit, and therefore, improving the recycling rates

560

of these two types of DW should be prioritized. The recycling potential for the other types of

561

DW should be improved in the following order: masonry-block, RC, concrete-brick, and

562

wood.

563

564

4. Conclusions

565

This study estimated the recycling potential considering both the environmental and

566

economic aspects according to building structure and DW types. The main contributions of

567

this study are as follows.

568

First, this study obtained reliable information about the characteristics of buildings and

569

quantities of materials in those buildings through direct surveys of 1,034 structures before

570

demolition. The DWGR data in this study are more systemic and reliable than previous

571

studies. The DWGR data in this study can be applied to devise suitable DW management

572

strategies and study DW generation and flow in detail. In addition, these data can help reduce

573

the uncertainty of results.

574

Second, this study provided an advanced approach to calculate the recycling potential. This

575

approach considers the structure of buildings, economic benefits, and environmental loads of

576

DW. The results showed that the recycling potential of the same DW differed according to the

577

structure. This study also presented the recycling potential according to building structure and

578

DW type for two recycling scenarios in Korea: current and maximum. These results can

579

promote a more detailed DW management strategy for governments and related industries.

580

The proposed approach can also be applied to other regions and countries.

581

Lastly, the results of the recycling potential are based on the DWGRs and CO2 emissions

582

according to building structure, CO2 emission flows according to DW type, and economic

583

values according to DW type. They present valuable information (i.e. operational cost and

584

CO2 emission by DW type and building structure) for stakeholders, such as the government,

585

industry, and academia. For example, the results of this study are useful to understand the

586

flow of CO2 emissions from recycled DW depending on the building structure. This

587

information can be fully utilized for studying the embodied energy and CO2 emissions of

588

buildings in future LCA studies. The carbon emission results according to DW type provided

589

by this study can be used as carbon footprint data of recycled building materials for

590

government and related industry stakeholders. The economic aspect can provide economic

591

data useful for stakeholders in related fields to establish economically efficient recycling

592

strategies. (Furthermore, this study can provide useful economic data for establishing

593

strategies for economically efficient recycling methods for interested parties in the related

594

fields.) In addition, the recycling potential results in this study can be used as a basis for

595

evaluating the environmental performance as a means of evaluating the economic value

596

considering carbon emissions in DW type and building structure. In other words, the results

597

of this study can be used to determine which recycled products are more environmentally

598

friendly and economically efficient, even for the same recycled product using the same DW

599

type. If the government and interested parties prepare waste resource recycling policies based

600

on the results of this study, this study could be used as a tool for sustainable development at a

601

social level as well. In addition, the concept of recycling potential that considers the types of

602

DWs and structures introduced in this study is more advanced than the existing recycling

603

potential concept (considering only types of wastes), which can contribute to improving the

604

level of awareness and knowledge for DWs. And the concept of recycling potential in this

605

study can reinforce the social responsibility demanded by relevant governments, corporations

606

and experts in terms of waste recycling. The recycling potential proposed in this study takes

607

into account the building structure, type of DWs, environmental cost, and economic cost,

608

which can be used as a means to enhance social responsibility for stakeholders in related

609

fields. In this respect, the results of this study contribute to social sustainability.

610

The DWGRs, CO2 emissions, and economic value of DW data in this study may differ by

611

region and country. In general, this limitation has always posed a theoretical and practical

612

problem in this field. Therefore, inventory data and DWGR information in this study can be

613

considered as having inherent limitations. Nevertheless, recent DWGR estimation studies

614

(Kleemann et al., 2016; Akhtar and Sarmah., 2018; Villoria Sáez et al., 2018; Wang et al.,

615

2019) will provide an opportunity to overcome the inherent limitations of this study. And the

616

advanced approach proposed to evaluate the recycling potential of DW in this study is

617

applicable to buildings in other regions and countries.

618

619

Acknowledgments

620

This work was supported by the National Research Foundation of Korea (NRF) grant funded

621

by the Korea government (MSIT) (NRF-2019R1A2C1088446).

622

This work was supported by the National Research Foundation of Korea (NRF) grant funded

623

by the Korea government (MSIP) (NRF- 2017R1D1A1B03033030).

624

This work was supported by “Human Resources Program in Energy Technology” of the

625

Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial

626

resource from the Ministry of Trade, Industry & Energy, Republic of Korea. (No.

627

20174030201740).

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Highlights

1. Reliable DW data were collected through field surveys of 736 residential buildings. 2. Even the same DW type, the CO2 emission differs depends on building structure type. 3. Recycling potential (RP) was calculated considering building structures and DW types. 4. Metals and masonry-block structure showed the highest RP in current situation. 5. RP of glass and wood structure is most likely to increase in Korea situation.

Credit Author Statement

1. Gi-Wook Cha (Methodology; Formal analysis; Writing - Original Draft) 2. Hyeun Jun Moon (Conceptualization; Supervision; Project administration) 3. Young-Chan Kim (Validation; Writing - Review & Editing) 4. Won-Hwa Hong (Resources; Funding acquisition) 5. Gyu-Yeob Jeon (Funding acquisition) 6. Young Ran Yoon (Data Curation) 7. Changha Hwang (Data Curation) 8. Jung-Ha Hwang (Writing - Review & Editing)

Declaration of Interest Statement

This paper does not include relevant financial (for example patent ownership, stock ownership, consultancies, speaker's fees), personal, political, intellectual, or religious interests.