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Volume 37, Issue 1 (2022)
GeoRes 2022, 37(1): 127-139 |
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Received: 2021/11/5 | Accepted: 2021/12/23 | Published: 2022/01/22
Received: 2021/11/5 | Accepted: 2021/12/23 | Published: 2022/01/22
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Farzi Dayeri A, Javid A, Ghaffarzadeh H, Hosseinzadeh Lotfi F. Comparative Study of Separation Management Model from Dry Waste Source with Methods of Referring to the Door of Production Bases and Use of the Reverse Vending Machine in the Western Regions of Tehran. GeoRes 2022; 37 (1) :127-139
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1- Department of Environmental Management, Islamic Azad University, Science and Research Branch, Tehran, Iran
2- Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
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Introduction
The expansion of cities, urbanization, and the gradual increase in the number of large cities worldwide, particularly in developing countries, including Iran, on the one hand, and urban growth, population concentration and agglomeration, along with increasing environmental and economic pressures on urban systems on the other, have led to greater attention being paid to cities and to the acceptance of their multiple roles and functions [Sharafi et al., 2016]. Among the most fundamental urban elements for enhancing citizens’ social welfare are urban services. The equitable distribution of urban services and, consequently, social justice constitute one of the most critical challenges facing most cities [Azizi Danalo & Mojtaba Zadeh, 2016]. Spatial justice refers to the fair distribution of urban services and facilities in order to achieve a balanced society, such that all citizens have adequate access, while also reducing time and financial costs for residents [Yaghfouri et al., 2017].
One of the adverse consequences of modern urbanization is the exposure of large populations to health and environmental hazards associated with waste [Kamiabi & Muslimi, 2020]. Achieving sustainable development and environmental protection necessitates the use of modern technologies that are cleaner and more environmentally friendly, as well as more accessible [Zahedi & Najafi, 2006]. Integrated waste management represents a comprehensive approach to resource and environmental management that has emerged from the application of the sustainable development concept [Geng et al., 2007]. With the increasing generation of waste in urban and rural communities, waste management systems are now considered an integral component of comprehensive management systems [Kamiabi & Muslimi, 2020]. Recycling is a cost-effective solution, as it imposes lower costs on municipalities compared to landfilling or incineration, while its core benefits include energy conservation and a cleaner environment. Given rapid population growth and the growing governmental emphasis on environmental protection, the management and recycling of dry waste have gained particular importance [Peyvastegar & Ansari, 2017].
In the Tehran metropolitan area, more than 6,500 tons of municipal solid waste are generated daily, approximately 13% of which, about 850 tons per day, originates from the western districts 5, 9, 21, and 22. The potential amount of source-separated dry waste in these districts is estimated at around 360 tons per day. By employing modern waste management systems, it is possible to manage this vast volume of waste and mitigate its associated environmental problems through improved urban cleanliness, mechanized waste collection, source separation programs, and increased capacity for processing and recycling municipal solid waste [Farzi Dayeri et al., 2021]. Door-to-door collection of dry waste at points of generation, the establishment of recycling kiosks, the use of reverse vending machines (RVMs), and the installation of multi-compartment recycling containers are among the urban service facilitation methods aimed at encouraging public participation in recycling and source separation within urban environments.
A number of studies have addressed recycling-related issues. Vatanparast et al. examined the site selection of urban dry waste exchange stations using GIS in the city of Mashhad, developing multiple information layers based on defined criteria and proposing four areas as the most suitable locations for station establishment [Vatanparast et al., 2012]. Rafiei et al. have ranked urban areas of Mashhad in terms of citizen participation in source separation of various types of dry waste into three categories, moderately developed, deprived, and advantaged, using multi-criteria mathematical programming [Rafiei et al., 2013]. Dehghani Kazemi have conducted a study on the application of group decision-making techniques, fuzzy logic, and GIS in locating waste stations in Tehran’s District 9. After identifying criteria using the classical Delphi technique, standard buffer distances were determined through the fuzzy Delphi method, and GIS was subsequently employed to apply these buffers within the study area, resulting in the identification of five suitable sites for recycling stations [Dehghani Kazemi et al., 2013]. Batouei and Gheidar Kheljani have evaluated and prioritized source separation options using the TOPSIS method in Shahid Rajaei Township, Tehran. Among 16 source separation methods, incentive-based approaches offering greater material benefits to citizens were found to be the most preferred [Batouei & Gheidar Kheljani, 2017]. Mohammadi et al. ranked 44 neighborhoods of Ardabil Municipality in terms of source separation indicators using the VIKOR model within a GIS environment, categorizing neighborhoods into four groups: desirable, relatively desirable, undesirable, and completely undesirable [Mohammadi et al., 2017]. Mirzaei and Cheraghalikhani have prioritized factors influencing the location of recycling kiosks as a method of source separation for dry waste in Tehran’s District 5 using the Analytic Hierarchy Process (AHP) and GIS software [Mirzaei & Cheraghalikhani, 2018]. Ilanloo et al. have conducted a study on optimal site selection for municipal waste recycling facilities in Kelardasht County to identify suitable locations for reducing recyclable waste volumes. In this study, five criteria and their allowable distances were determined using the fuzzy Delphi method and the deterministic center-of-gravity approach, while AHP and GIS were employed to determine criterion weights and produce zoning maps, ultimately identifying four suitable sites for recyclable solid waste recycling facilities [Ilanloo et al., 2019].
Fuzzy sets offer greater compatibility with linguistic and often ambiguous human judgments, and the use of fuzzy numbers enables long-term forecasting and real-world decision-making [Howarth & Monasterolo, 2016]. The fuzzy Delphi method seeks to integrate the traditional Delphi technique with fuzzy set theory [Kaufmann & Gupta, 1988]. This approach, derived from the combination of classical Delphi and fuzzy set theory, facilitates group decision-making by fostering a shared understanding of expert opinions [Samadi Miarkalai et al., 2017]. Its objective is to achieve the most reliable group consensus among experts on a specific topic through repeated questionnaire-based surveys and feedback [Montazer & Jafari, 2008]. Experts express their judgments in the form of triangular fuzzy numbers; subsequently, the mean of expert opinions and the degree of deviation of each expert’s view from the mean are calculated. These results are then returned to the experts for revision or confirmation of their judgments until the fuzzy mean values stabilize sufficiently [Forouzandeh et al., 2012]. Van Laarhoven and Pedrycz have proposed the fuzzy Analytic Hierarchy Process by replacing crisp values with triangular fuzzy numbers in pairwise comparison matrices, based on the logarithmic least squares method [van Laarhoven & Pedrycz, 1983]. Ishikawa et al. further have developed the Delphi technique using triangular fuzzy numbers [Ishikawa et al., 1993]. Chang introduces an integrated model combining AHP and fuzzy theory, known as the Fuzzy Analytic Hierarchy Process (FAHP). Owing to its strong compatibility with human cognitive processes and its mathematically grounded algorithm, this method demonstrates high efficiency and is now regarded as a modern decision-making approach [Chang, 1996]. Several studies emphasize the application of fuzzy logic within AHP to enhance alignment with real-world conditions [Kahraman et al., 2003].
A review of the literature reveals a notable research gap in modeling the management of source separation and collection of dry waste using the aforementioned methods. Existing studies have largely focused on other urban service land-use applications related to municipal waste management, such as landfill site selection, urban service stations, and recycling kiosks. Accordingly, the aim of this study, with an emphasis on improving the efficiency of recycling operations and dry waste collection, is to conduct a comparative assessment of dry waste source separation management models based on door-to-door collection at points of generation and the application of reverse vending machines in the western districts of Tehran.
Methodology
This study is applied in terms of purpose and descriptive–survey in nature and method. A mixed‐methods approach (qualitative–quantitative) was employed for data analysis. The research was conducted in 2020 in Municipal Districts 5, 9, 21, and 22 of Tehran, covering an area of more than 17,000 hectares.
To comparatively assess the efficiency of dry waste recycling, the fuzzy Delphi technique was first used to screen and predict the effective indicators of the source separation management model for dry waste. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was applied to determine the relative importance and weights of the selected criteria. After preparing indicator layers and overlaying them in the ArcGIS 10.7 environment, management modeling was ultimately performed using fuzzy logic inference, and the efficiency desirability of door-to-door collection at points of generation and the use of reverse vending machines (RVMs) was comparatively evaluated.
In the initial stage, expert opinions were used to identify and preliminarily determine the factors influencing the source separation management model based on door-to-door collection and the use of RVMs. Ten university faculty members with expertise in environmental studies, geography and urban planning, architecture and urban design, and economic and social sciences participated in this phase. After being informed about the research topic, each selected expert allocated approximately 80 minutes for in-depth interviews. Through discussions with this expert panel, the most influential keywords for preliminary modeling were extracted. These keywords were then aligned with spatial codes derived from a literature review, and, based on the research team’s assessment, 16 criteria were formulated and incorporated into an electronic questionnaire using Google Forms with a seven-point linguistic Likert scale. To obtain complementary expert opinions, the survey was administered to 35 experts over two Delphi rounds. To reduce ambiguity arising from uncertainty in decision-making, triangular fuzzy numbers corresponding to the seven linguistic scales were applied at all stages [Bouzon et al., 2016]. Expert judgments were collected using linguistic questionnaires with corresponding fuzzy scales and subsequently converted into triangular fuzzy numbers. In the next step, based on the aggregated fuzzy opinions of all experts, the fuzzy value of each indicator was defined using triangular membership functions. All calculations related to fuzzy valuation, defuzzification, and indicator importance were performed through formula programming in Excel 2016 [Liu, 2013].
In the second round of the fuzzy Delphi method, from the initial 16 criteria, 5 and 9 criteria were respectively identified and validated for inclusion in the management model for implementing dry waste source separation using the selected methods. Less important criteria were excluded due to defuzzified values below the threshold and low consensus levels. At this stage, because the retained indicators exceeded the threshold values, no new indicators were proposed, and an acceptable expert consensus level of 84% was achieved; therefore, the fuzzy Delphi process was terminated. To assess the reliability of the questionnaire used for indicator identification and screening, Cronbach’s alpha coefficient was calculated using SPSS 23. The resulting value of 0.982, close to 1, indicated very high reliability of the questionnaire applied in the fuzzy Delphi method.
After finalizing the criteria through the fuzzy Delphi method, eight steps were undertaken to determine criterion weights using the FAHP approach [Chang, 1996]: (1) developing a graphical representation of the hierarchical structure of the problem; (2) defining linguistic terms and their corresponding triangular fuzzy numbers [Kahraman, 2008]; (3) collecting expert judgments from 10 specialists for pairwise comparisons of criteria using a six-point linguistic scale questionnaire; (4) constructing fuzzy pairwise comparison matrices for each expert and generating the aggregated fuzzy matrix of expert opinions [Mikhailov, 2003]; (5) calculating a fuzzy number for each row of the pairwise comparison matrix; (6) computing the degree of possibility of fuzzy numbers relative to one another; (7) determining criterion weights from the pairwise comparison matrices; and (8) normalizing the resulting weight vector. All computations for determining criterion weights were carried out through programming in MATLAB 2017. In the FAHP technique, the consistency ratio was used to verify the validity of responses. A consistency ratio below 0.1 confirmed that the collected questionnaire data were reliable and consistent [Gogus & Boucher, 1998].
For modeling source separation management using door-to-door collection and the RVM model H11 (Tomra; China), the extracted indicators were integrated at a uniform spatial scale [Li & Weng, 2007]. Infrastructure compatibility/proximity indicators were derived at the pixel level, while population density, economic, social, citizen participation, and dry waste potential indicators were initially extracted at the census block level. To facilitate modeling, these indicators were first converted to the pixel level, similar to other variables, and all modeling procedures were performed at this spatial resolution.
To generate the dry waste production potential layer at the census block level, the following equation was used:
Pₚ = N × M × Z
where Pₚ denotes the potential amount of valuable dry waste per block (kg/day), N represents the block population (persons), M is the per capita waste generation rate (kg/person/day), and Z indicates the percentage of valuable dry waste potential.
After producing fuzzy maps for each criterion in GIS for the two management approaches, the criterion weights obtained through the FAHP technique were multiplied by the corresponding parameter layers, and a fuzzy–AHP integrated map was generated. By summing these weighted layers using the gamma operator and fuzzy overlay, the final management model map for dry waste source separation under the selected methods was produced. The applied techniques were adopted from previous studies [Lee et al., 2008; Pradhan, 2010; Sadeghi & Khalajmasoumi, 2015]. In addition, geostatistical methods were employed to examine the spatial variability of parameters [Kravchenko & Bullock, 1999].
Findings
The results of identifying and screening indicators using the fuzzy Delphi technique, together with the calculation and weighting of criteria affecting the source separation management model for dry waste through the Fuzzy Analytic Hierarchy Process, indicated the following:
a) The weighted contribution and priority of influential criteria in the management model based on door-to-door collection at points of generation were ranked as follows:
d) Proximity to cultural centers, chain stores, fruit and vegetable markets, and transportation terminals were identified as compatibility sub-criteria, and their effects were particularly evident in the management model based on RVM installation.
The analysis of fuzzy–AHP maps and the final management models, as well as the comparison of model efficiency, revealed the following outcomes:
Discussion
In the present study, the criteria of economic status, social and cultural status, citizen participation, and compatibility (proximity to shops, transportation terminals, cultural centers, and fruit and vegetable markets), in addition to other criteria, were respectively assigned mean weighted importance values of 0.1225, 0.1249, 0.1721, and 0.0598 for developing the efficiency models of source separation management methods. In contrast, Mirzaei and Cheraghalikhani (2018) have considered only four criteria of household density, overlap radius, accessibility, and the presence of a recycling booth in each neighborhood with weighted importance values of 0.38, 0.26, 0.50, and 0.20, respectively, as the main priorities for site selection, and assumed an operational and overlap radius of 500 m for each recycling booth. Vatanparast et al. (2012) have emphasized criteria such as population, education level, a one-kilometer distance between stations, accessibility, physical analysis of waste, and the level of citizen participation for locating urban dry waste exchange stations as source separation centers. These criteria are generally consistent with the effective criteria identified in the present study for the RVM-based source separation management model, with the difference that previous researchers focused mainly on geographic site-selection criteria and relied on classical logic and deterministic reasoning of respondents for decision-making in identifying, weighting indicators, and proposing models.
The findings of Mohammadi et al. (2017) indicate that 18.8% of Ardabil neighborhoods are in a desirable condition in terms of source separation indicators, while more than 80% are in an undesirable condition. In contrast, the results of the present study for the western districts of Tehran showed average desirable and undesirable efficiency levels of 76.5% and 23.5%, respectively, in the management models. This difference can be attributed to the greater potential for attracting citizen participation in Tehran through the provision of appropriate facilities and institutional structures by the municipality.
Based on a review of the limited previous studies, most of the results of this research differ from earlier investigations. In the study by Dehghani Kazemi et al. (2013), eight categories of criteria, including distance from residential, educational, and healthcare areas; rivers and waterways; roads and highways; parks and green spaces; cultural and religious sites; industrial areas; sports facilities; and airports are defined for locating recycling stations, with minimum distance thresholds ranging from 76 m for roads and waterways to 518 m for airports. Similarly, Ilanloo et al. (2019) have identified five categories of criteria including distance from residential and commercial areas, urban roads, rivers, hospitals and educational centers, hotels, banks, and administrative offices with distance ranges from an average of 100 m from roads and residential areas to 900 m from hospitals and schools. All of these criteria are considered incompatible, as they aimed to define exclusion buffers to avoid potential health and environmental risks associated with recycling facilities. In contrast, the criteria introduced in the present study, due to the nature of implementing source separation at origin through door-to-door collection and RVM installation, and the necessity of proximity to self-service machines and waste generation points, were all defined as compatible. Specifically, in the RVM-based approach, increasing distance beyond a 50 m overlap radius from locations such as fruit and vegetable markets, chain stores, passenger transportation terminals, and cultural centers leads to a reduction in the efficiency of the management model.
The findings of Rafiei et al. (2013) show that, on average, 80% of households in middle-income and affluent areas of Mashhad deliver their separated dry waste to vehicles visiting waste generation points, while 20% of citizens in affluent, middle-income, and deprived areas deliver their waste to fixed stations. In contrast, the results of the present study indicated that 87% of citizens in the western districts of Tehran had appropriate and desirable access to deliver dry waste to door-to-door collection vehicles, and 66% were also able to deliver their dry waste to RVMs. The higher level of citizen participation in Tehran compared to Mashhad can be attributed to notable differences in cultural, social, and economic contexts.
Batouei and Gheidar Kheljani (2017) have evaluated proposed methods for implementing source separation in Shahid Rajaei Town, Tehran, including door-to-door collection and the placement of single-purpose stations (mainly for paper) at specific locations, which are ranked 8 and 11 with closeness coefficients of 0.43 and 0.40, respectively. These findings are consistent with the results of the present study, confirming the higher efficiency of the door-to-door source separation management method compared with the RVM installation approach.
Greater efficiency, reduced likelihood of opinion exclusion, more appropriate consideration of preferential judgments, and increased convergence through expert opinions in identifying factors affecting the source separation management model across social, cultural, economic, and environmental dimensions constitute key reasons for employing the combined fuzzy Delphi and FAHP techniques integrated with GIS in this study to identify and spatially distribute the efficiency desirability of the management model.
The limited availability of comparable studies was one of the main limitations of this research. It is therefore recommended that future studies examine and compare other source separation management approaches, such as the establishment of surface and underground temporary storage facilities for dry waste, using alternative multi-criteria decision-making techniques including TOPSIS and neural networks.
Conclusion
Given the importance and necessity of efficiency in source separation of waste, the results of this study indicate that implementing a dry waste management model based on door-to-door collection at points of generation is more efficient, effective, and extensive across the studied districts than the approach based on installing self-service dry waste collection machines (RVMs).
Acknowledgments: Not applicable.
Ethical Permission: Not applicable.
Conflict of Interest: The present article is derived from the PhD dissertation of the first author entitled “Developing a Management Model for Dry Waste Recycling with the Location of Recycling Booths or Alternative Methods (Case Study: Western Districts of Tehran)”, conducted under the supervision of the second and third authors and consultation of the fourth author at Islamic Azad University, Science and Research Branch, Tehran.
Author Contributions: Farzi Dayeri AA (first author), Main Researcher/Introduction Writer/Discussion Writer/Data Analyst (50%); Javid AH (second author), Assistant Researcher/Methodologist (20%); Ghaffarzadeh HR (third author), Assistant Researcher/Methodologist (20%), Hosseinzadeh Lotfi F (fourth author), Assistant Researcher/Data Analyst (10%)
Funding: Not applicable.
The expansion of cities, urbanization, and the gradual increase in the number of large cities worldwide, particularly in developing countries, including Iran, on the one hand, and urban growth, population concentration and agglomeration, along with increasing environmental and economic pressures on urban systems on the other, have led to greater attention being paid to cities and to the acceptance of their multiple roles and functions [Sharafi et al., 2016]. Among the most fundamental urban elements for enhancing citizens’ social welfare are urban services. The equitable distribution of urban services and, consequently, social justice constitute one of the most critical challenges facing most cities [Azizi Danalo & Mojtaba Zadeh, 2016]. Spatial justice refers to the fair distribution of urban services and facilities in order to achieve a balanced society, such that all citizens have adequate access, while also reducing time and financial costs for residents [Yaghfouri et al., 2017].
One of the adverse consequences of modern urbanization is the exposure of large populations to health and environmental hazards associated with waste [Kamiabi & Muslimi, 2020]. Achieving sustainable development and environmental protection necessitates the use of modern technologies that are cleaner and more environmentally friendly, as well as more accessible [Zahedi & Najafi, 2006]. Integrated waste management represents a comprehensive approach to resource and environmental management that has emerged from the application of the sustainable development concept [Geng et al., 2007]. With the increasing generation of waste in urban and rural communities, waste management systems are now considered an integral component of comprehensive management systems [Kamiabi & Muslimi, 2020]. Recycling is a cost-effective solution, as it imposes lower costs on municipalities compared to landfilling or incineration, while its core benefits include energy conservation and a cleaner environment. Given rapid population growth and the growing governmental emphasis on environmental protection, the management and recycling of dry waste have gained particular importance [Peyvastegar & Ansari, 2017].
In the Tehran metropolitan area, more than 6,500 tons of municipal solid waste are generated daily, approximately 13% of which, about 850 tons per day, originates from the western districts 5, 9, 21, and 22. The potential amount of source-separated dry waste in these districts is estimated at around 360 tons per day. By employing modern waste management systems, it is possible to manage this vast volume of waste and mitigate its associated environmental problems through improved urban cleanliness, mechanized waste collection, source separation programs, and increased capacity for processing and recycling municipal solid waste [Farzi Dayeri et al., 2021]. Door-to-door collection of dry waste at points of generation, the establishment of recycling kiosks, the use of reverse vending machines (RVMs), and the installation of multi-compartment recycling containers are among the urban service facilitation methods aimed at encouraging public participation in recycling and source separation within urban environments.
A number of studies have addressed recycling-related issues. Vatanparast et al. examined the site selection of urban dry waste exchange stations using GIS in the city of Mashhad, developing multiple information layers based on defined criteria and proposing four areas as the most suitable locations for station establishment [Vatanparast et al., 2012]. Rafiei et al. have ranked urban areas of Mashhad in terms of citizen participation in source separation of various types of dry waste into three categories, moderately developed, deprived, and advantaged, using multi-criteria mathematical programming [Rafiei et al., 2013]. Dehghani Kazemi have conducted a study on the application of group decision-making techniques, fuzzy logic, and GIS in locating waste stations in Tehran’s District 9. After identifying criteria using the classical Delphi technique, standard buffer distances were determined through the fuzzy Delphi method, and GIS was subsequently employed to apply these buffers within the study area, resulting in the identification of five suitable sites for recycling stations [Dehghani Kazemi et al., 2013]. Batouei and Gheidar Kheljani have evaluated and prioritized source separation options using the TOPSIS method in Shahid Rajaei Township, Tehran. Among 16 source separation methods, incentive-based approaches offering greater material benefits to citizens were found to be the most preferred [Batouei & Gheidar Kheljani, 2017]. Mohammadi et al. ranked 44 neighborhoods of Ardabil Municipality in terms of source separation indicators using the VIKOR model within a GIS environment, categorizing neighborhoods into four groups: desirable, relatively desirable, undesirable, and completely undesirable [Mohammadi et al., 2017]. Mirzaei and Cheraghalikhani have prioritized factors influencing the location of recycling kiosks as a method of source separation for dry waste in Tehran’s District 5 using the Analytic Hierarchy Process (AHP) and GIS software [Mirzaei & Cheraghalikhani, 2018]. Ilanloo et al. have conducted a study on optimal site selection for municipal waste recycling facilities in Kelardasht County to identify suitable locations for reducing recyclable waste volumes. In this study, five criteria and their allowable distances were determined using the fuzzy Delphi method and the deterministic center-of-gravity approach, while AHP and GIS were employed to determine criterion weights and produce zoning maps, ultimately identifying four suitable sites for recyclable solid waste recycling facilities [Ilanloo et al., 2019].
Fuzzy sets offer greater compatibility with linguistic and often ambiguous human judgments, and the use of fuzzy numbers enables long-term forecasting and real-world decision-making [Howarth & Monasterolo, 2016]. The fuzzy Delphi method seeks to integrate the traditional Delphi technique with fuzzy set theory [Kaufmann & Gupta, 1988]. This approach, derived from the combination of classical Delphi and fuzzy set theory, facilitates group decision-making by fostering a shared understanding of expert opinions [Samadi Miarkalai et al., 2017]. Its objective is to achieve the most reliable group consensus among experts on a specific topic through repeated questionnaire-based surveys and feedback [Montazer & Jafari, 2008]. Experts express their judgments in the form of triangular fuzzy numbers; subsequently, the mean of expert opinions and the degree of deviation of each expert’s view from the mean are calculated. These results are then returned to the experts for revision or confirmation of their judgments until the fuzzy mean values stabilize sufficiently [Forouzandeh et al., 2012]. Van Laarhoven and Pedrycz have proposed the fuzzy Analytic Hierarchy Process by replacing crisp values with triangular fuzzy numbers in pairwise comparison matrices, based on the logarithmic least squares method [van Laarhoven & Pedrycz, 1983]. Ishikawa et al. further have developed the Delphi technique using triangular fuzzy numbers [Ishikawa et al., 1993]. Chang introduces an integrated model combining AHP and fuzzy theory, known as the Fuzzy Analytic Hierarchy Process (FAHP). Owing to its strong compatibility with human cognitive processes and its mathematically grounded algorithm, this method demonstrates high efficiency and is now regarded as a modern decision-making approach [Chang, 1996]. Several studies emphasize the application of fuzzy logic within AHP to enhance alignment with real-world conditions [Kahraman et al., 2003].
A review of the literature reveals a notable research gap in modeling the management of source separation and collection of dry waste using the aforementioned methods. Existing studies have largely focused on other urban service land-use applications related to municipal waste management, such as landfill site selection, urban service stations, and recycling kiosks. Accordingly, the aim of this study, with an emphasis on improving the efficiency of recycling operations and dry waste collection, is to conduct a comparative assessment of dry waste source separation management models based on door-to-door collection at points of generation and the application of reverse vending machines in the western districts of Tehran.
Methodology
This study is applied in terms of purpose and descriptive–survey in nature and method. A mixed‐methods approach (qualitative–quantitative) was employed for data analysis. The research was conducted in 2020 in Municipal Districts 5, 9, 21, and 22 of Tehran, covering an area of more than 17,000 hectares.
To comparatively assess the efficiency of dry waste recycling, the fuzzy Delphi technique was first used to screen and predict the effective indicators of the source separation management model for dry waste. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was applied to determine the relative importance and weights of the selected criteria. After preparing indicator layers and overlaying them in the ArcGIS 10.7 environment, management modeling was ultimately performed using fuzzy logic inference, and the efficiency desirability of door-to-door collection at points of generation and the use of reverse vending machines (RVMs) was comparatively evaluated.
In the initial stage, expert opinions were used to identify and preliminarily determine the factors influencing the source separation management model based on door-to-door collection and the use of RVMs. Ten university faculty members with expertise in environmental studies, geography and urban planning, architecture and urban design, and economic and social sciences participated in this phase. After being informed about the research topic, each selected expert allocated approximately 80 minutes for in-depth interviews. Through discussions with this expert panel, the most influential keywords for preliminary modeling were extracted. These keywords were then aligned with spatial codes derived from a literature review, and, based on the research team’s assessment, 16 criteria were formulated and incorporated into an electronic questionnaire using Google Forms with a seven-point linguistic Likert scale. To obtain complementary expert opinions, the survey was administered to 35 experts over two Delphi rounds. To reduce ambiguity arising from uncertainty in decision-making, triangular fuzzy numbers corresponding to the seven linguistic scales were applied at all stages [Bouzon et al., 2016]. Expert judgments were collected using linguistic questionnaires with corresponding fuzzy scales and subsequently converted into triangular fuzzy numbers. In the next step, based on the aggregated fuzzy opinions of all experts, the fuzzy value of each indicator was defined using triangular membership functions. All calculations related to fuzzy valuation, defuzzification, and indicator importance were performed through formula programming in Excel 2016 [Liu, 2013].
In the second round of the fuzzy Delphi method, from the initial 16 criteria, 5 and 9 criteria were respectively identified and validated for inclusion in the management model for implementing dry waste source separation using the selected methods. Less important criteria were excluded due to defuzzified values below the threshold and low consensus levels. At this stage, because the retained indicators exceeded the threshold values, no new indicators were proposed, and an acceptable expert consensus level of 84% was achieved; therefore, the fuzzy Delphi process was terminated. To assess the reliability of the questionnaire used for indicator identification and screening, Cronbach’s alpha coefficient was calculated using SPSS 23. The resulting value of 0.982, close to 1, indicated very high reliability of the questionnaire applied in the fuzzy Delphi method.
After finalizing the criteria through the fuzzy Delphi method, eight steps were undertaken to determine criterion weights using the FAHP approach [Chang, 1996]: (1) developing a graphical representation of the hierarchical structure of the problem; (2) defining linguistic terms and their corresponding triangular fuzzy numbers [Kahraman, 2008]; (3) collecting expert judgments from 10 specialists for pairwise comparisons of criteria using a six-point linguistic scale questionnaire; (4) constructing fuzzy pairwise comparison matrices for each expert and generating the aggregated fuzzy matrix of expert opinions [Mikhailov, 2003]; (5) calculating a fuzzy number for each row of the pairwise comparison matrix; (6) computing the degree of possibility of fuzzy numbers relative to one another; (7) determining criterion weights from the pairwise comparison matrices; and (8) normalizing the resulting weight vector. All computations for determining criterion weights were carried out through programming in MATLAB 2017. In the FAHP technique, the consistency ratio was used to verify the validity of responses. A consistency ratio below 0.1 confirmed that the collected questionnaire data were reliable and consistent [Gogus & Boucher, 1998].
For modeling source separation management using door-to-door collection and the RVM model H11 (Tomra; China), the extracted indicators were integrated at a uniform spatial scale [Li & Weng, 2007]. Infrastructure compatibility/proximity indicators were derived at the pixel level, while population density, economic, social, citizen participation, and dry waste potential indicators were initially extracted at the census block level. To facilitate modeling, these indicators were first converted to the pixel level, similar to other variables, and all modeling procedures were performed at this spatial resolution.
To generate the dry waste production potential layer at the census block level, the following equation was used:
Pₚ = N × M × Z
where Pₚ denotes the potential amount of valuable dry waste per block (kg/day), N represents the block population (persons), M is the per capita waste generation rate (kg/person/day), and Z indicates the percentage of valuable dry waste potential.
After producing fuzzy maps for each criterion in GIS for the two management approaches, the criterion weights obtained through the FAHP technique were multiplied by the corresponding parameter layers, and a fuzzy–AHP integrated map was generated. By summing these weighted layers using the gamma operator and fuzzy overlay, the final management model map for dry waste source separation under the selected methods was produced. The applied techniques were adopted from previous studies [Lee et al., 2008; Pradhan, 2010; Sadeghi & Khalajmasoumi, 2015]. In addition, geostatistical methods were employed to examine the spatial variability of parameters [Kravchenko & Bullock, 1999].
Findings
The results of identifying and screening indicators using the fuzzy Delphi technique, together with the calculation and weighting of criteria affecting the source separation management model for dry waste through the Fuzzy Analytic Hierarchy Process, indicated the following:
a) The weighted contribution and priority of influential criteria in the management model based on door-to-door collection at points of generation were ranked as follows:
- Population density (0.3590);
- Public participation (0.1955);
- Dry waste generation potential (0.1644);
- Social and cultural status of citizens (0.1419);
- Economic status of citizens (0.1392).
- Population density (0.2731);
- Public participation (0.1487);
- Dry waste generation potential (0.1251);
- Social and cultural status of citizens (0.1080);
- Economic status of citizens (0.1059);
- Proximity to fruit and vegetable markets (0.0806);
- Proximity to chain stores and commercial centers (0.0741);
- Proximity to cultural facilities (cultural centers, neighborhood houses, and cinema complexes) (0.0527);
- Proximity to passenger transportation terminals (0.0319).
d) Proximity to cultural centers, chain stores, fruit and vegetable markets, and transportation terminals were identified as compatibility sub-criteria, and their effects were particularly evident in the management model based on RVM installation.
The analysis of fuzzy–AHP maps and the final management models, as well as the comparison of model efficiency, revealed the following outcomes:
- In District 21 and the central part of District 5, citizens demonstrated higher participation in the implementation of dry waste source separation, while the lowest level of interaction with this program was observed across large areas of Districts 9 and 22.
- Population density in Districts 9 and 21 was higher than in Districts 5 and 22, and the influence of this indicator was clearly reflected in the source separation management model.
- The estimated dry waste generation potential showed a relatively uniform spatial distribution across the districts. However, due to higher per capita generation and a greater proportion of dry waste in the southeastern part of District 21, the desirability of this potential was particularly pronounced in that area.
- A comparison of the better economic conditions of citizens in District 5 and the eastern part of District 22 relative to Districts 9 and 21 indicated that this indicator exerted an inverse effect on participation in source separation within the management model.
- The social and cultural status of citizens in Districts 5, 21, and 22 was more favorable for implementing source separation compared with District 9.
- The operational coverage of source separation implementation in compatible locations, considering service center locations and distance, was relatively uniform across the districts. Owing to the need for appropriate site selection that ensures security and operational feasibility of RVMs, the influence of compatibility factors was particularly evident in this management approach.
- The implementation of dry waste source separation management through door-to-door collection and RVM installation was identified as efficient and desirable across approximately 87% and 66% of the total study area, respectively.
- The door-to-door collection method exhibited higher efficiency in Districts 5, 21, and 22 compared with District 9. Citizens in District 9 showed limited willingness to cooperate with the municipality in implementing source separation through the examined methods, and dry waste was instead delivered to unauthorized and traditional collectors.
- The efficiency of source separation implementation using RVMs was unsatisfactory across most areas of District 9.
Discussion
In the present study, the criteria of economic status, social and cultural status, citizen participation, and compatibility (proximity to shops, transportation terminals, cultural centers, and fruit and vegetable markets), in addition to other criteria, were respectively assigned mean weighted importance values of 0.1225, 0.1249, 0.1721, and 0.0598 for developing the efficiency models of source separation management methods. In contrast, Mirzaei and Cheraghalikhani (2018) have considered only four criteria of household density, overlap radius, accessibility, and the presence of a recycling booth in each neighborhood with weighted importance values of 0.38, 0.26, 0.50, and 0.20, respectively, as the main priorities for site selection, and assumed an operational and overlap radius of 500 m for each recycling booth. Vatanparast et al. (2012) have emphasized criteria such as population, education level, a one-kilometer distance between stations, accessibility, physical analysis of waste, and the level of citizen participation for locating urban dry waste exchange stations as source separation centers. These criteria are generally consistent with the effective criteria identified in the present study for the RVM-based source separation management model, with the difference that previous researchers focused mainly on geographic site-selection criteria and relied on classical logic and deterministic reasoning of respondents for decision-making in identifying, weighting indicators, and proposing models.
The findings of Mohammadi et al. (2017) indicate that 18.8% of Ardabil neighborhoods are in a desirable condition in terms of source separation indicators, while more than 80% are in an undesirable condition. In contrast, the results of the present study for the western districts of Tehran showed average desirable and undesirable efficiency levels of 76.5% and 23.5%, respectively, in the management models. This difference can be attributed to the greater potential for attracting citizen participation in Tehran through the provision of appropriate facilities and institutional structures by the municipality.
Based on a review of the limited previous studies, most of the results of this research differ from earlier investigations. In the study by Dehghani Kazemi et al. (2013), eight categories of criteria, including distance from residential, educational, and healthcare areas; rivers and waterways; roads and highways; parks and green spaces; cultural and religious sites; industrial areas; sports facilities; and airports are defined for locating recycling stations, with minimum distance thresholds ranging from 76 m for roads and waterways to 518 m for airports. Similarly, Ilanloo et al. (2019) have identified five categories of criteria including distance from residential and commercial areas, urban roads, rivers, hospitals and educational centers, hotels, banks, and administrative offices with distance ranges from an average of 100 m from roads and residential areas to 900 m from hospitals and schools. All of these criteria are considered incompatible, as they aimed to define exclusion buffers to avoid potential health and environmental risks associated with recycling facilities. In contrast, the criteria introduced in the present study, due to the nature of implementing source separation at origin through door-to-door collection and RVM installation, and the necessity of proximity to self-service machines and waste generation points, were all defined as compatible. Specifically, in the RVM-based approach, increasing distance beyond a 50 m overlap radius from locations such as fruit and vegetable markets, chain stores, passenger transportation terminals, and cultural centers leads to a reduction in the efficiency of the management model.
The findings of Rafiei et al. (2013) show that, on average, 80% of households in middle-income and affluent areas of Mashhad deliver their separated dry waste to vehicles visiting waste generation points, while 20% of citizens in affluent, middle-income, and deprived areas deliver their waste to fixed stations. In contrast, the results of the present study indicated that 87% of citizens in the western districts of Tehran had appropriate and desirable access to deliver dry waste to door-to-door collection vehicles, and 66% were also able to deliver their dry waste to RVMs. The higher level of citizen participation in Tehran compared to Mashhad can be attributed to notable differences in cultural, social, and economic contexts.
Batouei and Gheidar Kheljani (2017) have evaluated proposed methods for implementing source separation in Shahid Rajaei Town, Tehran, including door-to-door collection and the placement of single-purpose stations (mainly for paper) at specific locations, which are ranked 8 and 11 with closeness coefficients of 0.43 and 0.40, respectively. These findings are consistent with the results of the present study, confirming the higher efficiency of the door-to-door source separation management method compared with the RVM installation approach.
Greater efficiency, reduced likelihood of opinion exclusion, more appropriate consideration of preferential judgments, and increased convergence through expert opinions in identifying factors affecting the source separation management model across social, cultural, economic, and environmental dimensions constitute key reasons for employing the combined fuzzy Delphi and FAHP techniques integrated with GIS in this study to identify and spatially distribute the efficiency desirability of the management model.
The limited availability of comparable studies was one of the main limitations of this research. It is therefore recommended that future studies examine and compare other source separation management approaches, such as the establishment of surface and underground temporary storage facilities for dry waste, using alternative multi-criteria decision-making techniques including TOPSIS and neural networks.
Conclusion
Given the importance and necessity of efficiency in source separation of waste, the results of this study indicate that implementing a dry waste management model based on door-to-door collection at points of generation is more efficient, effective, and extensive across the studied districts than the approach based on installing self-service dry waste collection machines (RVMs).
Acknowledgments: Not applicable.
Ethical Permission: Not applicable.
Conflict of Interest: The present article is derived from the PhD dissertation of the first author entitled “Developing a Management Model for Dry Waste Recycling with the Location of Recycling Booths or Alternative Methods (Case Study: Western Districts of Tehran)”, conducted under the supervision of the second and third authors and consultation of the fourth author at Islamic Azad University, Science and Research Branch, Tehran.
Author Contributions: Farzi Dayeri AA (first author), Main Researcher/Introduction Writer/Discussion Writer/Data Analyst (50%); Javid AH (second author), Assistant Researcher/Methodologist (20%); Ghaffarzadeh HR (third author), Assistant Researcher/Methodologist (20%), Hosseinzadeh Lotfi F (fourth author), Assistant Researcher/Data Analyst (10%)
Funding: Not applicable.
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