Management of the construction and demolition waste (CDW) and determination of the best disposal alternative by FAHP (Fuzzy Analytic Hierarchy Process): A case study of Tehran, Iran

ABSTRACT

The study focused on the management of the final disposal of Construction and Demolition Waste (CDW) generated in Tehran and the determination of the best disposal method. For this purpose, three of final disposal alternatives such as reusing, recycling and landfilling were selected. Moreover, three effective criteria (environmental, economic and socio-cultural) and 16 sub-criteria were considered. A group of experts participated in the questionnaire in order to create a database. FAHP (Fuzzy Analytic Hierarchy Process) was used to determine the final disposal alternative considering to the sustainable development approach. The results obtained from the FAHP model showed that the weight of the environmental, economic and socio-cultural criteria was 0.330, 0.544 and 0.126, respectively. In the view of the environmental, the weight value of the sub-criteria of recyclable, water pollution, air pollution, soil pollution and natural resources protection were 0.035, 0.127, 0.069, 0.042 and 0.055, respectively. In terms of economic, the weight value of the sub-criteria of raw materials cost, land occupancy rate, profitability, mutual interests, exploitation cost and initial investment were 0.108, 0.045, 0.063, 0.083, 0.094 and 0.149 respectively. In addition, from the point of view of socio-cultural aspect, the weight value of the sub-criteria of community acceptance, government cooperation, people’s awareness level, security in construction and employment were 0.015, 0.050, 0.011, 0.022, and 0.026, respectively. The reuse alternative with a weight of 0.439 was selected as the best disposal method and the recycling (0.312) and landfilling (0.250) were second and third alternatives, respectively. The results also indicated that the generated CDW in Tehran was mostly composed of reusable components such as metals, plastics, wood, glass and gypsum. Therefore, with the selection of this alternative as a final disposal method, the costs of raw materials and the pollution originated from landfilling can be significantly reduced.

Implication: The main purpose of this study is to provide a framework in which the priority of criteria and sub-criteria and alternatives in CDW management in Tehran, Iran is determined. The novelty of this method included providing an efficient management method in CDW management, because the production of this type of waste in Iran has become a major problem. The most important part of this method was the decision of local experts to provide the best disposal alternative, since solving problems related to CDW management is achieved by participation and collaboration with experts working in the same system. The obtained results showed that reusing is the first priority in terms of all the studied criteria and sanitary landfilling is the last priority. Sanitary landfilling is currently in place in the study area and respondents are well aware of its disadvantages. The results in terms of each criterion show that economic criteria are the most important criteria. Investment cost in terms of economic criteria, public acceptance in terms of social criteria and water pollution in terms of environmental criteria as the most effective sub-criteria according to the main goal. Various complex factors affect CDW management systems and therefore the use of practical decision-making techniques such as FAHP to deal with the complexity of CDW management will be useful and valuable.

Introduction

Construction and demolition waste (CDW) is described as a material that is mostly generated from construction and demolition (C&D) activities and also civil and urban development projects. Its improper management causes the adverse economic, environmental and social impacts (Tchobanoglous 2009). CDW usually includes concrete, asphalt, gypsum, metals, non-stony fraction (plastics, wood, paper, organic materials and glass) and some hazardous wastes as lubricants, oils and greases (Galán et al. 2019). Many factors affect the production of CDW related to the construction of residential buildings, which include the economic situation of the people, different seasons, different urban areas, population growth and the urban development (Najafpoor et al. 2014). CDW is considered as the main element of municipal solid waste (MSW), which is responsible for 25% to 40% of the produced MSW in developing and developed countries (Xu et al. 2019). Integrated CDW management is an essential element in preserving our natural resources, environment, society and economy (Yazdani et al. 2021). The management of CDW including the activities such as waste generation, waste collection, waste storage, waste processing and waste disposal (Lin et al. 2020). The CDW landfilling causes soil, air and water pollution, and has greenhouse gas emissions and as a result of global warming (Kabirifar et al. 2020). The CDW management hierarchy including reduce, reuse, and recycle strategies is the most efficient way of CDW disposal (Kabirifar et al. 2020). To establish a suitable system for CDW management, it is essential to consider several factors based on sustainable development, including environmental impacts, economic costs and benefits, and socio-cultural factors and also the relationship between each of these components (Soltani et al. 2015). The integration of all these factors in order to effectively plan and comprehensively evaluate alternatives by decision makers, requires appropriate methods and tools such as multi-criteria decision making (MCDM) techniques (Soltani et al. 2015). Because CDW management strategies are so diverse, choosing a single CDW management approach or sequence that meets the goals of decision makers is challenging (Past, Mesdaghinia, and Naderi 2016). Decision makers should compare CDW management strategies based on their level of performance in meeting defined criteria (Soltani et al. 2015). There are various frameworks for decision making in CDW management (Alimohammadi and Naderi 2021; Dahlbo et al. 2015). Oyenuga et al. considered appropriate decision-making models for optimizing the management of CDW (16). Moreover, Achillas et al. used three economic, social, and environmental criteria for decision-making in CDW management (17). There are several alternatives for managing CDW, including reuse, recycling and landfilling. Each alternative for CDW management has different environmental, technical, social and economic characteristics (Khoshand et al. 2020). In order to choose the most appropriate alternative in CDW management, all aspects of each and its advantages and disadvantages in terms of environmental, cultural, social and economic issues must be considered (Khoshand et al. 2020). AHP is used as an efficient technique to deal with complex decision problems, especially when quantitative and qualitative aspects need to be considered (Khoshand et al. 2020). In a study, Tot et al. conducted a study evaluating the factors influencing the sustainable development of waste management using AHP (Tot et al. 2016). However, the AHP is unable to take into account the ambiguity of decision makers’ judgment of numerical values. One of the common features of decision issues is fuzzy. For this purpose, the Fuzzy Analytic Hierarchy Process (FAHP) technique has been proposed to solve this problem (Mdallal and Hammad 2019). This technique enables decision makers to represent approximate preferences with fuzzy numbers (Khoshand et al. 2020). Mdallal et al. proposed a holistic fuzzy AHP approach as a multi-criteria decision-making tool for evaluating and selecting the optimum alternative to reduce concrete waste in construction sites (Mdallal and Hammad 2019).

Recently, various studies have been conducted in many cities of Iran in the field of CDW management. In these studies, the generation rate of these wastes and also their disposal alternatives have been evaluated. In a study, Nikmehr et al. investigated the major factors affecting CDW sites in Iran (Nikmehr et al. 2015). Asgari et al. evaluated the quality and quantity of CDW in Tehran (Asgari et al. 2017). Moreover, Ansari et al. evaluated the quantitative and qualitative of CDW in Yazd (Ansari and Ehrampoush 2018). In another study, Khoshand et al. established a novel framework based on the FAHP approach in order to assess different CDW management alternatives in Tehran. In their study, the alternatives of landfilling, recycling, reusing, and reduction were investigated with respect to 16 different individual criteria (Khoshand et al. 2020). Similarly, Khodaverdi et al. also used a fuzzy analysis network process approach to evaluate concrete waste management alternatives (Khodaverdi, Faghih, and Eslami 2008). Although, in the studies all criteria and sub-criteria of decision-making have not been comprehensively evaluated and investigated. In the past few years, Tehran’s urban administration has reduced the environmental concerns by planning to establish CDW recovery facilities to recycle materials such as gravel, sand, etc. Unfortunately, until now, a comprehensive and integrated management method has not been provided in selecting the best alternative for disposal of CDW, and this lack of attention to the prioritization of disposal alternatives has caused an increase in economic costs. A low recycling rate indicated that the education programs and public participation for waste reduction and recycling in recent years have not been efficient and a revision should be made to the CDW disposal program (Majlessi et al. 2019). The study focused on managing the final disposal of CDW generated in Tehran, prioritizing and choosing the best disposal alternative using a FAHP model.

Background of CDW management in Tehran/Iran

In Tehran, about 82,646,051 m³ of CDW (average 16,529,210 m³ per year) were generated during 2011 to 2016 which only about 26% of them has been recycled. Mixing sand and cement, concrete, broken bricks and soil have the highest amount of the composition of CDW in Tehran that was 30, 19, 18 and 11%, respectively. Based on the previous studies, about 2,784,158 t of the waste will generate in 2025 and this is approximately 122% higher than wastes generate in 2016 (Asgari et al. 2017). Currently in Tehran, an average of about 50,000 tons per day of construction and demolition wastes are produced from which over 30,000 tons per day are landfilled. More than 57% of these wastes are placed in non-dangerous waste category and have the potential for being recycled and reused (Broujeni et al. 2016). The generated MSW per capita per day in Tehran is 0.96 kg and 76% of the MSW is landfilled. Furthermore, produced CDW per capita per day is 5.2 kg and 81% of them are landfilled (Bigdeloo, Mousavi, and Moeinaddini 2020). The composition of the generated CDW in Tehran was mainly of soil (11%), broken bricks (18%), concrete (19%), and sand and cement mixture (30%).

Currently, there is practically no special system to separate and reduce the source of CDW in Tehran, and in a completely traditional way, valuable waste is separated by the property owner or the demolition contractor, and all valuable components such as glass, metal parts (including doors and windows), cooler channels, types of pipes, etc., are accompanied by components that cannot be separated on site (Past et al., 2017). The CDW are separated at the demolition site and they leave the flow of waste management and the rest enter the flow of CDW management system. At present, 6 sand recovery centers, including: Tehran Shan, Moin Puyendgan, Road and Asphalt Company, Boland Payeh, Rigsazzan Sahra Sand and Mase Company, are operating in Tehran for the processing of CDW. These processing centers receive 5000 to 10,000 tons of CDW as daily (Asgari et al. 2017). More than 50,000 tons/d CDW is transported to the CDW processing and recovery centers of Kahrizak and Abali. A sand recycling unit with a capacity of about 4,000 tons and a MSW incinerator with a capacity of 300 tons to generate electricity were located in the centers. Kahrizak center receives an average of 8,000 tons of different types of waste from different production sources such as healthcare and medical centers, concentrated treated wastewater sludge and CDW from the 22 regions of Tehran. Abali is the largest construction and civil waste disposal center in Tehran and due to its special location. According to the latest statistics of the officials of Abali center, more than 1,500 trucks of CDW are transported to this area every day, and a total of 4,000 units of the debris are unloaded here. Due to the numerous numbers of constructions, renovation and demolition projects, a significant amount of CDW are generated in Tehran. Considering the lack of sufficient and suitable land for CDW disposal, it is necessary to establish an integrated of CDW management in Tehran (Asgari et al. 2017). The required data in this study is collected from Kahrizak and Abali. Disposal centers (Asgari et al. 2017).

Materials and methods

The location of the study site

Tehran is the capital of Iran and the most crowded city in Iran. Tehran is located on the south of the Alborz mountains (latitude of 35° 34“to 35° 50” N and longitude of 51° 08“to 51° 37”

E) and covers 664 km2 (land area) with a population of 8,429,807. The solid waste processing and recycling center of Kahrizak (“Aradkouh”) with an area of nearly 14,000,000 m² is located in the south of Kahrizak region. After weighing, MSW is either transferred to solid waste processing units for recycling or compost production, or transferred to landfills. On average, 8000 tons of different types of waste are collected daily from 22 districts of Tehran, towns and surrounding cities and transported to this center. The area of Abali solid waste disposal center is 5,400,000 m², where 3,300 tons of construction waste is transported there daily. The General Waste Management Act has been in place in Iran since 2004, which also covers CDW management (Asgari et al. 2017). It should be noted that these general rules do not apply to CDW management. CDW management in Tehran mainly suffers from lack of budget allocated to CDW management, lack of an effective CDW management program, lack of regulations in the field of CDW management, lack of specialized staff in implementing the CDW management plan and also limited people.

The CDW management stages in the study

This study was conducted in September 2020 to September 2021. In order to carry out the present study, the following stages have been taken in order:

1. Studying books, articles and regulations related to CDW management

2. Refer to the waste management organization of Tehran city, the vice-department of CDW in order to receive information and data on CDW management

3. Investigating CDW management in Tehran based on the received information

4. In order to identify the effective factors on the disposal of CDW, all the studies in this field were reviewed

5. Then, the influential criteria were compiled with attention to the perspective of sustainable development and the opinion of the experts and managers

6. A questionnaire in order to collect suitable data with the research method prepared and regulated

7. For weighting, criteria, sub-criteria and alternatives, questions were designed and prepared in the form of a pairwise comparison according to the nine-hour table and distributed and collected among experts related to the subject

8. After collecting the data, using the hierarchical analysis method, which is one of the multi-criteria decision making techniques, the criteria and alternatives were weighted.

9. And in the continuation of the research and after determining the weight of the criteria and alternatives, the prioritization of CDW disposal methods was performed by the researcher using software package Expert Choice version 11.

Determining the CDW disposal criteria, sub-criteria and alternatives

The data required in this study have been collected by referring to the Waste Management Organization (WMO) and the Construction and Critical Waste Centre (CCWC) as well as specialized questionnaires using a hierarchical analysis method. In order to collect relevant data and information to investigate the management of CDW in Tehran, after administrative and organizational coordination, the required data and information were obtained, and also the researcher compiled questionnaires for considering the best method of disposal of CDW in Tehran using of a type of the multi-criteria decision-making technique among solid waste experts in 3 groups including:

1. Managers and solid waste experts in the waste management organization

2. Distinguished professors in the field of solid waste management

3. The students of the Faculty of Health and Environment

Fuzzy AHP approach

This technique allows decision makers to turn complex decision problems into a hierarchical cluster, especially when the decision problem involves multiple alternatives.The use of a fixed judgment scale is the main weakness of the AHP method, which causes the inability of the method to address the uncertainty and unevenness in performing pairwise comparisons (Goulart Coelho, Lange, and Coelho 2017). Fuzzy AHP has been proposed to address the problem of determining the compatibility of preferences in the AHP method. In order to prioritize each decision variable over the other variable in FAHP, linguistic variables are converted to fuzzy numbers (Table 1). The first step in the proposed FAHP model is to determine the alternatives and criteria. For this purpose, a comprehensive literature review was conducted and most of the alternative and criteria were extracted through previous studies (Bovea and Powell 2016). According to the criteria and alternatives presented in these studies and considering economic and technological aspects by experts, the criteria and alternatives of this study were selected and analyzed and decided using a questionnaire and hierarchical model. The part of the questionnaire that is related to the pairwise comparison of the main criteria is shown in Table 2. Based on the table, the main criteria were compared in pairs and were scored from 1 to 9 according to the degree of importance. The scores were 1 (having the same preference), 3 (almost important), 5 (important), 7 (very important), 9 (completely important) and 2, 4, 6 (intermediate) (Khoshand et al. 2020). In this study, each judgment in pairwise comparisons is expressed by linguistic variables, and triangular fuzzy numbers (TFNs) are used to calculate the weights. TFN can be denoted by (v, p, t) where “v” stands for lower value, “p” for higher value and “t” for medal value in each fuzzy event. Each of the language variables and their associated TFNs are presented in Table 2. It should be noted that these values are M1, M2, M4, M6 and M8 and the values of M3, M5, M7 and M9 are considered as intermediate values for comparisons. The matrix of fuzzy evaluation (M_n ×_n =(E_ij)_n can be derived as follows

Table 1. Conversion scale of Triangular Fuzzy Numbers (TFNs), each judgment in pairwise comparisons is expressed by linguistic variables and TFNs are used to calculate the weights.

Variable	Linguistic description of variable	TFN
M1	Without preference	(1, 1, 2)
M2	Moderate preference	(1, 2, 3)
M4	Strong preference	(3, 4, 5)
M6	Very strong preference	(5, 6, 7)
M8	Full preference	(7, 8, 9)

Table 2. Pairwise comparisons of main criteria, 1 (having the same preference), 3 (almost important), 5 (important), 7 (very important), 9 (completely important) and 2, 4, 6 (intermediate).

Criteria	Completely important						Intermediate important					Completely						Criteria
Social	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Environmental
Social	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Economic
Environmental	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Economic

$M=\left[\begin{array}{c}\begin{array}{ccc}\left(\mathrm{1.1.1}\right)& \left(v_{12}.p_{12}.t_{12}\right)\dots & \left(v_{1n}.p_{1n}.t_{1n}\right)\\ \left(v_{21}.p_{21}.t_{21}\right)& \left(\mathrm{1.1.1}\right)\dots & \left(v_{2n}.p_{2n}.t_{2n}\right)\\ \dots & \dots & \dots \end{array}\\ \left(v_{1n}.p_{1n}.t_{1n}\right)\left(v_{n2}.p_{n2}.t_{n2})\dots \text{leftright}(\mathrm{1.1.1}\right)\end{array}\right]$

In the matrix of fuzzy evaluation, $E_{ij}=\left(v_{ij},p_{ij},t_{ij}\right)$ describes the relative importance of the x_i object over the u_j goal. Moreover, for all I and j, E_ii⁻¹ = (1/t_ij, 1/p_ij, 1/v_ij).

The last stage in the FAHP model is analytical evaluation. The alternatives were compared to each other in terms of each criterion or sub-criterion. Each criterion or sub-criterion is compared with the others based on the main purpose of the study. In the analytical evaluation, H=^{22 … ,hn} is the goal set, each object was taken and then extent analysis was conducted for each goal. For each object, m extent analysis values can be derived as following equation (Chang et al. 2007);

(1) $E_{h_1}^1.E_{h_2}^2\dots .E_{h_1}^{m}i=1.2\dots .n$(1)

In the above equation, $E_{g_1}^j\left(j=1,2,\dots ,m\right)$ represents TFNs. The weight vector of a comparison matrix according to Chang’s extent analysis method is determined through the next steps (Chang et al. 2007).

Step I: The value of the fuzzy synthetic extent regarding the ith object is determined as

$C_i=\sum _{j=1}^m{E}_{g_1}^j\otimes \sum _{i=1}^n\sum _{j=1}^m{\left[E_{g_1}^j\right]}^{-1}$

$=\left[\sum _{j=1}^m{v}_j.\sum _{j=1}^m{p}_j.\sum _{j=1}^m{t}_j\right]\otimes \left[\frac{1}{{\sum }_{i=1}^n{t}_i},\frac{1}{{\sum }_{i=1}^{n}p},\frac{1}{{\sum }_{i=1}^n{v}_i}\right]$

Step II: The degree of possibility of E₂= (v₂, p₂, t₂)$\ge$ E₁= (v₁, p₁, t₁) is expressed as

$F\left(E_2\ge E_1\right)=hgt\left(E_1\cap E_2\right)$

$={\mu }_{E_2}\left(a\right)=\left\{\begin{array}{c}1if{p}_2\ge p_1\\ 0if{v}_1\ge v_2\\ \frac{v_1-t_2}{\left(p_2-t_2\right)-(p_2-v_1)}otherwise\end{array}\right.$

The ordinate of the maximum intersection point between ${\mu }_{E1}$and ${\mu }_{E2}$ is a. It should be noted that the comparison between E₁ and E₂ is possible only when values of both F (E₁ $\ge$ E₂) and F (E₂ $\ge$ E₁) are determined.

Step III: The possibility degree when a convex fuzzy number will be more than k convex fuzzy numbers E_i (i = 1, 2, … , k) can be represented as the following.

(2) $\left(E\ge E_1.E_2\dots ..E_k\right)=F\left[\begin{array}{c}\left(E\ge E_1\right)and\left(E\ge E_2\right)\\ and\dots and\left(E\ge E_k\right)\end{array}\right]=\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{F}\left(E\ge E_i\right).i=\mathrm{1.2.3}\dots k$(2)

In this study, the incompatibility coefficient was determined using the matrix eigenvalue method.

(3) $A\ast w_i={\lambda }_{max}\ast w_i,i=1,2,\dots ,n$(3)

(4) $CI=\frac{{\lambda }_{max}-n}{n-1}$(4)

(5) $CR=\frac{CI}{RI}$(5)

The maximum specific value of the matrix is n and the number of rows or columns. Dividing the Compatibility Index (CI) by the Random Index (RI) gives the compatibility rate. The compatibility index is obtained from the interpolation of random matrices with degree n. If the adjustment rate is less than 0.1, it indicates that the judgments made are consistent; otherwise the judgments need to be reconsidered. In the end, from the combination of relative weights, alternatives and criteria, the final weights for each level were identified.

Results and discussion

The hierarchical structure of the proposed model consists of four different clusters, including the main objective, criteria and sub-criteria, and alternatives. Creating a database and judging was the next step in the proposed FAHP model. For this, a questionnaire was used to create the database of the study. In addition, numerous meetings were held with the respondents in order to conduct the questionnaire survey to evaluate criteria and alternatives and make decisions about them. The members of this meeting included politicians, managers, experts and professors in the field of solid waste management. All the criteria and alternatives were comprehensively explained to the respondents in order to increase their awareness of the decision-making problem as well as their understanding of the criteria and alternatives. It should be noted that previous studies have suggested holding group meetings along with using a questionnaire as a practical method in judging decision-making and weighting inference issues. Khodaverdi et al. conducted a study on the evaluation of concrete waste management alternatives using the fuzzy analytical network method. In their study the weight matrices of criteria and sub-criteria were made using Fuzzy numbers. Their evaluation was done by a group of decision makers from different levels such as the government, non-governmental organizations and people with regard to creating an acceptable disposal alternative (Khodaverdi, Faghih, and Eslami 2008). The study evaluated the possible and practical alternatives for disposal of CDW from the perspective of sustainable development according to environmental, economic and socio-cultural criteria (Figure 1).

Figure 1. Sustainable development in CDW management based on the reusing, recycling and landfilling alternatives.

The criteria and sub-criteria weighting

In this study, the environmental criterion and its sub-criteria (soil pollution, water pollution, air pollution, amount of recyclable materials and conservation of natural resources), the economic criterion and its sub-criteria (raw materials cost, land occupancy rate, profitability, common interests, operating and maintenance costs and initial investment) and the socio-cultural and its sub-criteria (community acceptability, government cooperation, public knowledge, building security and job creation) were investigated (Figure 2). Overall, the 16 sub-criteria were selected as the most effective sub-criteria as a subset of environmental, economic and socio-cultural criteria. The environmental and socio-cultural criteria each included the 5 sub-criteria and economic criteria contained the 6 sub-criteria (Table 3). The priority weights of the studied criteria were extracted using a descriptive method. It should be noted that higher weight criteria are more important in the decision-making process. The weight of the sub-criteria of the all criteria (environmental (Z), economic (E) and socio-cultural (S)) in choosing the best disposal alternative has been indicated in Table 3 and Figure 3.

Figure 2. Hierarchy structure of CDW management alternatives in terms of criteria and sub-criteria.

Figure 3. The weight of the sub-criteria of the all criteria (environmental (Z), economic (E) and socio-cultural (S)) in selecting the best disposal alternative.

Table 3. Incompatibility coefficient and the weight value of the criteria (environmental, economic and socio-cultural criteria) and sub-criteria (the criteria and sub-criteria with higher weights are more significant in the decision making).

Criteria	Weight	Incompatibility rate	Sub-criteria	Weight	Incompatibility rate
Environmental	0.330	0.009	Recyclable (Z1)	0.035	0.04
			Water pollution (Z2)	0.127
			Air pollution (Z3)	0.069
			Soil pollution (Z4)	0.042
			Natural resources protection (Z5)	0.055
Economic	0.544	0.009	Raw materials cost (E1)	0.108	0.02
			Land occupancy rate (E2)	0.045
			Profitability (E3)	0.063
			Mutual interests (E4)	0.083
			Exploitation cost (E5)	0.094
			Initial investment (E6)	0.149
Socio-cultural	0.126	0.009	Community acceptance (S1)	0.015	0.03
			Government cooperation (S2)	0.050
			People’s awareness level (S3)	0.011
			Security in construction (S4)	0.022
			Employment (S5)	0.026

The weight of the environmental, economic and socio-cultural criteria was 0.330, 0.544 and 0.126, respectively (Table 3). The results showed that the economic criterion with the weight of 0.544 was the highest weight among the studied criteria. The weight of the raw materials cost, land occupancy rate, profitability, mutual interests, exploitation cost and initial investment sub-criteria were obtained 0.108, 0.045, 0.063, 0.083, 0.094 and 0.149 respectively. Among the sub-criteria of economic criteria, the initial investment cost was reported the highest with the weight of 0.149 and the land occupation coefficient was the lowest with the weight of 0.045. The implementation of any solid waste management system is associated with a significant investment cost (Farzanegan and Hayo 2019). The disposal methods with lower investment costs can provide the more benefits for investors (Oliver, Kothari, and Mays 2019). Furthermore, the studied disposal centers have been facing difficult economic conditions for several years, which make investment cost factor as the highest priority among all economic sub-criteria be considered (Ghorbani Dastgerdi, Yusof, and Shahbaz 2018). The economic implications of CDW are particularly significant because construction materials account for approximately 40% of material flows in the global economy. In addition, material costs account for 50–60% of the total cost of a construction project (Chileshe et al. 2018; Khanh and Kim 2015). However, approximately 20–30% of construction materials are wasted during the construction phase and sent to landfills (Marrero et al. 2017). The economic aspect of CDW management mainly includes costs related to material use, landfill taxes, productivity loss, disposal costs, transportation and overhead costs, recycling and reuses costs, operating costs of recycling facilities and etc (Ghisellini et al. 2018). According to Lockrey et al., economic viability is a fundamental factor that significantly affects the performance and behavior of CDW management practitioners (Lockrey et al. 2016). In addition, Chen et al. proposed economic concerns as the most influential factor in CDW management from a governmental and institutional perspective (Chen, Hua, and Liu 2019). In another study, Yuan emphasized the role of economic concerns regarding the slow and inefficient process of waste recycling in recycling facilities (Yuan 2017). In a study, Khoshand et al. proposed a novel framework based on the Fuzzy AHP approach in order to assess different CDW management alternatives in Tehran. In their study proposed alternatives (including landfilling, recycling, reusing, and reduction) were investigated with respect to 16 different individual criteria. The criteria were divided into four different groups, namely environmental, social, technical, and economic. Their results indicated that the economic criteria with the priority weight of 0.51 were the highest weight that their study confirmed the results of the present study (Khoshand et al. 2020).

The obtained results indicated that the environmental criterion with the priority weight of 0.330 was considered as the second significant criterion (Table 3). The weight of the recyclable, water pollution, air pollution, soil pollution and natural resources protection sub-criteria were reported 0.035, 0.127, 0.069, 0.042 and 0.055, respectively (Table 3). The results showed that the water pollution sub-criterion with the weight of 0.384 had the highest and the recyclable materials with the weight of 0.109 had the lowest impact on the environmental criterion. The importance of groundwater and surface water pollution in terms of environmental damage had the greatest impact on the selection of the best disposal method and the sub-criteria of the air pollution and natural resources protection were the next priorities, respectively (Table 3). Various studies have also addressed the environmental concerns associated with CDW, such as soil degradation, water pollution, and global warming (Barbudo et al. 2020; Jain et al. 2020). According to Ding et al., each square meter of CDW filled in the ground leads to 53 grams of soil degradation and about 1.5 tons of groundwater loss (Ding et al. 2016). Tehran has many environmental problems, which means that it is known as a polluted city (Tahbaz 2016). The CDW discharges have been reported in unsuitable locations such as roadsides, which can cause a number of environmental problems such as air, water and soil pollution (Asgari et al. 2017).

The results showed that the socio-cultural criterion with the weight of 0.126 was the most insignificant criterion in the decision making process. The weight of the community acceptance, government cooperation, people’s awareness level, security in construction and employment sub-criteria were 0.015, 0.050, 0.011, 0.022, and 0.026, respectively (Table 3). The sub-criterion of government cooperation with a weight of 0.398 had the most and the level of knowledge of the people with a weight of 0.093 had the least effect. In other words, government cooperation socially had the greatest impact on choosing the best method of disposal, and job creation was the next priority. A major obstacle to the development and implementation of CDW management methods is the assumption that these practices lead to increased project costs (Negash et al. 2021). Lockrey et al highlighted the role of contractors’ limited knowledge, awareness and insufficient community participation as the main barriers to implementing CDW management methods (Lockrey et al. 2016). Similarly, Abarca-Guerrero, et al. stated that social awareness is an effective factor in achieving CDW management (Abarca-Guerrero, Maas, and Van Twillert 2017). In this regard, when CDW management stakeholders believe that waste generation is necessary, it is inefficient and challenging to implement sustainable strategies (Mahpour 2018). Moreover, Blaisi et al. proposed the lack of commitment, insufficient cooperation, and poor understanding among CDWM practitioners as challenges that prevent CDWM from achieving social sustainability (Blaisi 2019). In addition, health and safety issues related to material recycling from collection to transport and recycling, public awareness, aspirations and satisfaction toward CDW management, decisions and attitudes of CDW stakeholders, public participation in CDW management CDWM actions, and social concerns with illegal dumping (Abarca-Guerrero, Maas, and Van Twillert 2017). Nikmehr et al. revealed the vital role of culture and perceptions of practitioners based on a single quantitative method (Nikmehr et al. 2017).

The results indicated that the economic criterion with a weight of 0.544 had the highest and the social criterion with a weight of 0.126 had the least impact on the best choice of disposal method. The incompatibility rate of pairwise comparisons related to all criteria was less than 0.1, which indicates the consistency of decisions in the hierarchical analysis process (Table 3). The highest value of incompatibility was related to the environmental criterion with 0.04 and the lowest value was related to the economic criterion with 0.02. The incompatibility rate for determining the overall weight of the criteria was 0.009 (Table 3). Khodaverdi et al. in Iran reported that environmental aspects are associated with a higher total score. Their study showed that when the technical aspects are considered as a criterion, the priority is shifted toward the operational and management problems according to the documented tests of the selected recycling options. However, it should be noted that the relative weight for financial feasibility is relatively high, while the social aspects of choosing the recycling alternative are less than the environmental, financial and operational and management aspects (Khodaverdi, Faghih, and Eslami 2008).

The alternatives weighting

The sustainable development in CDW management based on the reusing, recycling and landfilling alternatives has been shown in Figure 1. According to the environment criterion, the weight of the reusing, recycling and landfilling alternatives were 0.429, 0.373 and 0.198, respectively that the highest priority for the best disposal method was the reusing alternative (Table 3). The relative importance of each alternative compared to the other alternatives based on the environment sub-criteria (soil pollution, water pollution, air pollution, amount of recyclable materials and conservation of natural resources) has been demonstrated in Figure 4.

Figure 4. The relative importance of each alternative compared to other alternatives in terms of the environmental sub-criteria (water pollution, air pollution, soil pollution, recyclable materials and conservation of natural resources).

According to the environmental criteria, disposal alternatives were compared in pairs by considering the relevant sub-criteria. The importance of each alternative is shown as a weight index in Figure 4. The result showed that considering the sub-criterion of water pollution, the reusing alternative with a weight of 0.80 had the highest importance. In addition, according to the sub-criterion of air pollution, the most important was related to the landfilling alternative with a weight of 0.65. Besides, from the point of view of recyclability, the highest degree of importance was obtained for the alternative of reusing, and by comparison based on the sub-criterion of the natural resources conversation the importance of the alternatives of reusing and recycling was reported to be the same (Figure 4). The inefficient management of CDW creates harmful effects on the environment by occupying land resources as landfills, producing harmful pollutants that endanger the atmosphere, and occupying already limited natural resources (Blaisi 2019; Borghi, Pantini, and Rigamonti 2018). For example, landfills are responsible for large amounts of methane gases through the decomposition of mixed CDW overtime, which is more harmful than CO₂ in terms of global warming effects (Jamaludin 2017; Oreto et al. 2021).

In Iran, Hormozi et al. investigated the geotechnical characteristics of recycled combined construction and demolition waste (RCCDW) at Fooladshahr (located in the Isfahan province, Iran) to determine whether they are an appropriate candidate in road base. Their results indicated that after initial recycling and resizing, residues have several remarkable characteristics for use in the base and sub-base layers (Kalantar Hormozi et al. 2021).

Based on the economic criterion, the weight of the reusing, recycling and landfilling alternatives were obtained 0.429, 0.274 and 0.235, respectively, which the highest priority associated with the reusing alternative (Table 4). The relative importance of each alternative compared to the other alternatives in terms of the economic sub-criteria (raw materials cost, land occupancy rate, profitability, common interests, operating and maintenance costs and initial investment) has been presented in Figure 5. The results of this study showed that considering all the economic sub-criteria except for the operating and maintenance costs and profitability, the highest weight was reported for the reuse alternative. In terms of the operating maintenance costs, the landfilling alternative was the most important, and in terms of profitability, the recycling was the most important alternative (Figure 5). This is because in the reuse alternative, the consumer’s capital is saved, but in the recycling alternative, the same product or specific waste is recycled and sold to the consumer again, which results in more profitability for recycling centers. The results showed that the main concern of the respondents to choose a suitable alternative to CDW management in Tehran is economic issues.

Figure 5. The relative importance of each alternative compared to the other alternatives (landfilling, recycling and reusing) in terms of the economic sub-criteria (operating and maintenance costs, initial investment, common interests, profitability, land occupancy rate, raw materials cost).

Table 4. The weight value of the alternatives (reusing, recycling and landfilling) based on the environmental, economic, socio-cultural criteria (the alternative with higher weight is more significant in the decision making).

Criteria	Alternative	Weight
Environmental	Reusing	0.429
	Recycling	0.373
	Landfilling	0.198
Economical	Reusing	0.492
	Recycling	0.274
	Landfilling	0.235
Socio-Cultural	Reusing	0.222
	Recycling	0.279
	Landfilling	0.500

And, according to the socio-cultural criterion, the weight of the reusing, recycling and landfilling alternatives were 0.222, 0.279 and 0.500, respectively that the highest priority was the sanitary landfilling alternative (Table 4). The relative importance of each alternative compared to other alternatives in terms of socio-cultural sub-criteria (community acceptability, government cooperation, public knowledge, building security and job creation) was depicted in Figure 6. The results showed that considering all the socio-cultural criterion except the job creation, the highest weight was reported for the landfilling alternative (Figure 6).

Figure 6. The relative importance of each alternative compared to other alternatives (landfilling, recycling and reusing) in terms of the socio-cultural sub-criteria (public knowledge, job creation, building security, government cooperation, community acceptability).

Choosing the landfilling alternative for CDW reduces the need to build centers and facilities for processing and recovery of these wastes, and as a result, the need for manpower is reduced, which in turn reduces the job creation factor.

The obtained results of the study revealed that the final priority of the alternatives according to the impact of all criteria (environmental, economic and socio-cultural criteria) and sub-criteria were reusing, recycling and landfilling, respectively. The reusing with the final weight of 0.439 was selected as the best disposal alternative and the recycling and landfilling alternatives with the weights of 0.312 and 0.250 were considered as the second and third alternative, respectively (Table 5). The CDW inorganic fraction was usually considered as an inert and reusable substance, which leads to the reuse of CDW, which is one of the most suitable alternatives in CDW management in the study area. One of the most important reasons for choosing the reuse alternative as the best choice for disposal is to reduce the initial investment, no need to occupy land, reduce initial costs and finally prevent water and soil pollution. The reusing alternative has partially been practiced in Tehran (Gálvez-Martos et al. 2018). Ulubeyli et al. indicated that more than 50% of the produced CDW is recyclable. However, this rate strongly depends on the nature of the CDW (Ulubeyli, Kazaz, and Arslan 2017). In another study, Yeheyis et al. studied CDW management in Canada. Their study proposed the CDW management frameworks that can maximize reducing, reusing, and recycling alternatives and minimize landfilling alternative as the sustainable framework (Yeheyis et al. 2013). Furthermore, Coronado et al. surveyed the potential of four different MCDM approaches or selecting the most appropriate CDW management alternative in Spain (Coronado-Hernández et al. 2020). In their study the CDW management alternative were recycling and landfilling. Their results showed that the best and the worst alternative were recycling and landfilling, respectively (Coronado-Hernández et al. 2020). The results of their study were similar to the results of this study, in which the landfilling alternative was chosen as the last disposal alternative. Various studies have reported landfilling as the last alternative to CDW management, which was mainly identified due to numerous disadvantages (Yeheyis et al. 2013). Taghipour et al. evaluated the CDW and its management challenges in Tabriz, Iran. Their results revealed that there was a great urgent need for applying specific practical policies, rules, and regulations for 3 R (reduce, reuse, and recycle) of CDW. Moreover, they proposed a central disposal for the management of the CDW according to the environmental and health considerations (Taghipour et al. 2019).

Table 5. The final priority of the alternatives according to the impact of all criteria (environmental, economic and socio-cultural criteria) and sub-criteria (The criteria and sub-criteria with higher weights are more significant in the decision making).

Alternative	Final Weight	Rank
Reusing	0.439	1
Recycling	0.312	2
Landfilling	0.250	3

The most widely used the disposal alternative of CDW in Tehran is currently landfilling, so that more than 70% of generated CDW is discharged for several years in both controlled and uncontrolled disposal sites (Asgari et al. 2017). Therefore, it is necessary to change the CDW management approach and replace the landfilling alternative with reusing and recycling alternatives. This management approach can prevent pollution caused by landfilling and return economic benefits to the government through the reusing and recycling of CDW, and increase individual and social confidence.

Conclusion

FAHP (Fuzzy Analytical Hierarchy Process) is one of the widely used methods in multi-criteria decision making (MCDM) in recent years. The technique has been used for weighing various factors such as quality, lead time, cost, energy use, waste minimization, emission, and social contribution, and weights of the factors have been considered for selecting the best alternative. In FAHP, experts compare pairs of criteria and if the number of criteria to be compared is large, there may be ambiguity in the comparisons, leading to inconsistencies. Some researchers have tried to overcome this issue by considering both global and local measures to reduce the number of measures that must be compared pairwise in each matrix. The practical application of the proposed technique is the optimization of orders among various disposal alternatives while taking into consideration all three perspectives of sustainability – economic, social, and environmental. The major advantage of this technique is that it can be used for both qualitative and quantitative measurements. The pairwise comparison used in this work reduces the dependence of the model on human judgments.

In the present study, three different CDW management alternatives, four criteria and 16 sub-criteria were selected based on extensive literature review and expert viewpoint and opinions. The data of the study was established through a questionnaire survey and the relative significance of alternatives with respect to each criterion was assessed. The obtained results showed that reusing alternative was the first priority in terms of all the studied criteria and the landfilling alternative was the last priority. The results in terms of each criterion show that economic criteria are the most important criteria. In summary, the investment cost sub-criterion in the economic criteria, the sub-criterion of public acceptance in the socio-cultural criteria and also the water pollution sub-criterion in the environmental criteria were considered as the most effective sub-criteria in CDW management. Various complex factors affect CDW management systems and therefore the use of practical decision-making techniques such as FAHP to deal with the complexity of CDW management will be useful and valuable, especially in developing countries such as Iran.

Acknowledgment

Furthermore, we appreciate the collaboration of the Department of Environmental Health Engineering Laboratories of the Tehran University of Medical Sciences.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability Statement

All data generated or analyzed during this study are included in the manuscript and its supplementary information files.

Supplementary Information

Supplemental data for this paper can be accessed online at https://doi.org/10.1080/10962247.2023.2178542

Additional information

Funding

The work was supported by the Institute for Environmental Research (IER), Tehran University of Medical Sciences [95-29815].

Notes on contributors

Vida Past

Vida Past is a research scholar from the Environmental Health Engineering Department at the Faculty of Health, the Tehran University of Medical Sciences, Tehran, Iran.

Kamiar Yaghmaeian

Kamiar Yaghmaeian is a professor from the Environmental Health Engineering Department at the Faculty of Health, the Tehran University of Medical Sciences, Tehran, Iran.

Maziar Naderi

Maziar Naderi is a research scholar from the Environmental Health Engineering Department at the Faculty of Health, the Tehran University of Medical Sciences, Tehran, Iran.

Nahal Naderi

Nahal Naderi is a research scholar from the Industrial Management Department at the Faculty of Management, the Tehran University, Tehran, Iran.