Promoting sustainability in Urban waste management in Amman for a circular economy

Mohammad A. Shbool; Ammar Al-Bazi; Leen S. Jebril; Noha M. Nasrallah; Salwa A. Al-Amad; Basem O. Al-Souliman

doi:10.1007/s10163-025-02405-2

Promoting sustainability in Urban waste management in Amman for a circular economy

Mohammad A. Shbool
, Ammar Al-Bazi^*
, Leen S. Jebril
, Noha M. Nasrallah
, Salwa A. Al-Amad
, Basem O. Al-Souliman

^*Corresponding author for this work

University of Jordan

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

11 Downloads (Pure)

Abstract

Amman, Jordan, faces escalating challenges in municipal solid waste management due to rapid urbanisation, population growth, and limited recycling participation. This study develops a novel decision-support framework that combines a System Dynamics (SD) model with fuzzy Analytic Hierarchy Process (AHP) and Artificial Neural Network (ANN) validation. The model explicitly integrates population trends, social awareness, recycling initiatives, and informal waste picker contributions into municipal waste forecasting. Social awareness was quantified using a fuzzy AHP survey of households, and its influence on source sorting behaviours was embedded as a dynamic feedback variable. Model validation demonstrates that the SD model achieved 94.3% prediction accuracy, outperforming the ANN’s 91.5%. Scenario testing showed that increasing household participation in source sorting by 20% annually reduced the growth rate of waste generation from 2.56% to 1.38%, diverting more than 60,000 tonnes from landfill by 2030. These findings underscore the critical role of behavioural interventions, beyond technical solutions, in reducing landfill dependency. By embedding social and behavioural variables within a predictive modelling framework, this study contributes a replicable tool for policymakers in Amman and other rapidly urbanising cities to advance circular economy strategies and long-term landfill planning.

Original language	English
Pages (from-to)	176-198
Number of pages	23
Journal	Journal of Material Cycles and Waste Management
Volume	28
Issue number	1
DOIs	https://doi.org/10.1007/s10163-025-02405-2
Publication status	Published - 18 Oct 2025

Bibliographical note

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Data Access Statement

Data are available from the corresponding author upon reasonable request.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 8 Decent Work and Economic Growth
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production

Keywords

Solid waste management
Circular economy
Social awareness
Source sorting
System dynamics
Waste prediction model

Access to Document

10.1007/s10163-025-02405-2

Promoting sustainability in Urban waste management in Amman for a circular economy
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Final published version, 3.31 MBLicence: CC BY 4.0

Cite this

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title = "Promoting sustainability in Urban waste management in Amman for a circular economy",

abstract = "Amman, Jordan, faces escalating challenges in municipal solid waste management due to rapid urbanisation, population growth, and limited recycling participation. This study develops a novel decision-support framework that combines a System Dynamics (SD) model with fuzzy Analytic Hierarchy Process (AHP) and Artificial Neural Network (ANN) validation. The model explicitly integrates population trends, social awareness, recycling initiatives, and informal waste picker contributions into municipal waste forecasting. Social awareness was quantified using a fuzzy AHP survey of households, and its influence on source sorting behaviours was embedded as a dynamic feedback variable. Model validation demonstrates that the SD model achieved 94.3\% prediction accuracy, outperforming the ANN{\textquoteright}s 91.5\%. Scenario testing showed that increasing household participation in source sorting by 20\% annually reduced the growth rate of waste generation from 2.56\% to 1.38\%, diverting more than 60,000 tonnes from landfill by 2030. These findings underscore the critical role of behavioural interventions, beyond technical solutions, in reducing landfill dependency. By embedding social and behavioural variables within a predictive modelling framework, this study contributes a replicable tool for policymakers in Amman and other rapidly urbanising cities to advance circular economy strategies and long-term landfill planning.",

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author = "Shbool, \{Mohammad A.\} and Ammar Al-Bazi and Jebril, \{Leen S.\} and Nasrallah, \{Noha M.\} and Al-Amad, \{Salwa A.\} and Al-Souliman, \{Basem O.\}",

note = "This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article{\textquoteright}s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article{\textquoteright}s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.",

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AU - Al-Amad, Salwa A.

AU - Al-Souliman, Basem O.

N1 - This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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N2 - Amman, Jordan, faces escalating challenges in municipal solid waste management due to rapid urbanisation, population growth, and limited recycling participation. This study develops a novel decision-support framework that combines a System Dynamics (SD) model with fuzzy Analytic Hierarchy Process (AHP) and Artificial Neural Network (ANN) validation. The model explicitly integrates population trends, social awareness, recycling initiatives, and informal waste picker contributions into municipal waste forecasting. Social awareness was quantified using a fuzzy AHP survey of households, and its influence on source sorting behaviours was embedded as a dynamic feedback variable. Model validation demonstrates that the SD model achieved 94.3% prediction accuracy, outperforming the ANN’s 91.5%. Scenario testing showed that increasing household participation in source sorting by 20% annually reduced the growth rate of waste generation from 2.56% to 1.38%, diverting more than 60,000 tonnes from landfill by 2030. These findings underscore the critical role of behavioural interventions, beyond technical solutions, in reducing landfill dependency. By embedding social and behavioural variables within a predictive modelling framework, this study contributes a replicable tool for policymakers in Amman and other rapidly urbanising cities to advance circular economy strategies and long-term landfill planning.

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JO - Journal of Material Cycles and Waste Management

JF - Journal of Material Cycles and Waste Management

IS - 1

ER -

Promoting sustainability in Urban waste management in Amman for a circular economy

Abstract

Bibliographical note

Data Access Statement

UN SDGs

Keywords

Access to Document

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Cite this