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Volume 37, Issue 3 (2022)
GeoRes 2022, 37(3): 419-428 |
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Received: 2022/06/22 | Accepted: 2022/08/21 | Published: 2022/07/1
Received: 2022/06/22 | Accepted: 2022/08/21 | Published: 2022/07/1
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Moniri F, Asghari H, Poursheikhan A, Hasani-Mehr S. Role of Low-Carbon Components in Transportation of Jolfa and Jananlo Cities, Iran, (Aras Free Region) using a Future Research Approach. GeoRes 2022; 37 (3) :419-428
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1- Department of Geography and Urban Planning, Astara Branch, Islamic Azad University, Astara, Iran
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Introduction
Recently, global climate change resulting from the excessive consumption of fossil energy has attracted increasing attention from the international community [Gokgoz & Guvercin, 2018]. As the principal driver of global climate change, the rapid rise in greenhouse gas (GHG) emissions has not only led to global warming, sea-level rise, and climatic variability, but has also exerted substantial adverse impacts on human health and economic development [Tang et al., 2018; Karlsson & Ziebarth, 2018]. Therefore, reducing GHG emissions and promoting low-carbon economic development are imperative. Cities, as regional or even national hubs, play a significant role in economic, political, cultural, and social development. At the same time, they are major consumers of local resources and primary sources of GHG emissions [Khanna et al., 2014]. Consequently, the key to reducing global GHG emissions lies in cities [Sudmant et al., 2016]. Studies indicate that the majority of energy consumption occurs in urban areas [Kean Fong et al., 2008]. Hosting more than half of the world’s population, cities function as the main centers of economic activity and energy use. Although they occupy only about 2% of the Earth’s surface, they account for approximately 75% of global energy consumption and nearly 80% of GHG emissions [Zheng et al., 2011].
The United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol serve as platforms for collectively addressing this global issue and its impacts. In addition to these two platforms, the Paris Agreement was adopted by the Conference of the Parties to the UNFCCC and approved by consensus in Paris on December 12, 2015. This agreement was the outcome of intensive negotiations that began in Bali in 2007 and lasted for more than eight years. Its overarching objectives include holding the increase in the global average temperature well below 2°C and pursuing efforts to limit the increase to 1.5°C above pre-industrial levels; enhancing adaptive capacity to climate change impacts; strengthening climate resilience; and fostering low-GHG emission development pathways without threatening food production, while aligning financial flows with low-emission and climate-resilient development. The Agreement incorporates the principles of “equity” and “Nationally Determined Contributions (NDCs),” allowing each country to set its own targets according to its capacities while pursuing sustainable development goals. In particular, climate action in this context requires enhanced transfer of scientific knowledge, research, and initiatives, which substantially facilitate the effective implementation of national environmental actions [Sereenonchai et al., 2020].
To combat climate change and achieve sustainable development goals, Low-Carbon Cities (LCCs) have emerged as one of the vital initiatives proposed and implemented globally under the UNFCCC framework. This initiative seeks to reshape human behavior and national economies to reduce dependence on carbon-intensive activities while achieving GHG emission reductions without constraining economic growth. The development of low-carbon cities has thus become an essential global response to the threats posed by climate change [Glaeser & Kahn, 2010; Tan et al., 2017; Fu et al., 2021]. Liu et al. [2017] argue that low-carbon city development is a process of public participation that requires concerted efforts by governments, enterprises, and individuals to reduce carbon emissions. The concept of the low-carbon city constitutes an integral component of sustainable development [Khanna et al., 2014]. Carbon emissions can be effectively reduced through the adoption of low-carbon development measures without undermining urban economic growth.
Although many countries and regions have now prioritized carbon reduction, the concept of the “low-carbon city” remains relatively nascent, and consensus on its definition has yet to be reached [While et al., 2010]. In practice, a low-carbon city provides a sustainability framework, and the theoretical and practical advancement of sustainable development is increasingly achievable through the realization of low-carbon cities. Fundamentally, low-carbon cities are those that implement serious and effective measures to mitigate environmental impacts and emissions. Low-carbon strategies, combining specific urban development objectives with constraints, should be promoted incrementally and in phases. This process requires substantial systemic transformations, including changes in infrastructure, institutions, and user practices [Wimbady et al., 2021].
The transport sector’s dependence on fossil fuels has driven the proliferation of internal combustion engine vehicles over the past century. This, in turn, has stimulated the expansion of infrastructure and low-density urban forms, which have increased private vehicle ownership and carbon dioxide (CO₂) emissions from mobility [Seto et al., 2014]. Meanwhile, many cities worldwide, particularly in Asia and North America still suffer from limited access to public transportation. The Organisation for Economic Co-operation and Development (OECD) estimates that cities with populations exceeding 300,000 accounted for 20% of CO₂ emissions from transport and passenger mobility in 2014 alone [Wimbady et al., 2021]. Statistics indicate that approximately 19% of global energy consumption and more than one quarter of global CO₂ emissions are attributable to transport, with emissions from public transport increasing faster than those from other sectors. Studies by the International Energy Agency (IEA) show that the transport sector is the largest energy consumer [Ebadinia et al., 2016]. Iran also represents a significant share in this sector. According to the Statistical Yearbook (latest edition, 2016), total CO₂ emissions in Iran amounted to 586 million tons in 2015, of which 30% originated from power plants affiliated with the Ministry of Energy, the private sector, and large industries; 25% from transport; 24% from residential, commercial, and public sectors; and 16% from industrial fuel consumption [Statistical Center of Iran, 2016].
Various indicators have been proposed to facilitate the establishment of low-carbon cities. Low-carbon urban development is a complex system encompassing infrastructure, industry, technology, and energy [Wang et al., 2018]. Numerous studies have examined effective approaches to low-carbon city development in specific domains, such as infrastructure strategies and energy consumption [Silver & Marvin, 2017; Ohnishi et al., 2018], as well as financial support mechanisms [Van der Heijden, 2017]. Zhang et al. [2021] have identified factors including available water resources, renewable energy consumption, CO₂ offsetting, nature-based solutions with a focus on process management, reduction of arable land expansion, urban green spaces, waste recycling capacity, CO₂ removal capacity, and urban waste treatment as key determinants of low-carbon city development in China. According to Li et al. [2021], the implementation of low-carbon city initiatives in China is feasible through reductions in energy consumption, upgrading of industrial structures, and advancement of technological innovation. Ahmad Ali et al. [2020] emphasize the reform of energy consumption patterns in the construction sector as a critical factor in reducing urban carbon emissions. Fraker [2013] highlights appropriate urban form, convenient access to public transport, extensive facilities for promoting cycling and walking, and reduced reliance on private vehicles as essential elements for achieving a low-carbon urban future through transport reform.
Factors such as the region’s distinctive geo-economic position; its location along the Silk Road; its role as a commercial crossroads between Europe and Central Asia; the presence of well-developed transport and communication networks in the hinterland and connections to major road networks and the electrified Tabriz–Jolfa railway; proximity to the Caspian and Black Seas; the presence of the Jolfa Customs Office (a first-tier national gateway); industrial estates; border markets; the Saint Stepanos Monastery; and major tourism destinations within the Aras Free Zone collectively underscore the critical importance of the transport sector in the cities of the Aras Free Zone. Given these conditions, high traffic volumes, particularly dependence on private vehicles and limited inclination toward public transport for urban and interurban travel have accentuated the role of transport in CO₂ emissions and air pollution. This highlights the necessity of investigating this issue to better understand the problem and to propose practical strategies for air pollution reduction. Accordingly, Moniri et al. [2022] also have emphasized the role of transport in the Jolfa and Jananlu regions and the importance of examining this factor in the low-carbonization of air quality. In this context, the primary objective of the present study is to analyze the role of transport in achieving low-carbon and carbon-free cities in the Aras Free Zone. Specifically, the study seeks to answer the following question: What are the most influential parameters affecting low-carbonization (with an emphasis on transport) in the Aras Free Zone (the cities of Jolfa and Jananlu)?
Methodology
This study is descriptive–analytical in nature and was conducted in 2021 using the cross-impact analysis method. The spatial scope of the research is the Aras Free Zone. The Aras Free Zone has been planned over an area of approximately 51,000 hectares along the Aras River. It encompasses parts of the counties of Jolfa and Khoda Afarin, located along Iran’s borders with Azerbaijan, Armenia, and Nakhchivan. The Aras Free Zone consists of four independent yet interconnected areas. Its core area, covering 20,500 hectares, is located in Jolfa County, while three detached zones, Qali Beyglu (24,000 ha), Khoda Afarin (6,100 ha), and Norduz (240 ha), collectively form the remaining extent of the Aras Free Zone. With Jolfa as its central city, the Aras Free Zone is situated along the historic Silk Road corridor. According to the latest national population and housing census, the city of Jolfa has a population of 8,810 comprising 2,547 households, while the city of Jananlu has a population of 1,742, including 555 households [Statistical Center of Iran, 2016].
Structural cross-impact analysis is one of the most widely used foresight methods. After adopting a systems-based approach and demonstrating its analytical capacity, it experienced significant development in the late 1960s and was further advanced through Jay Forrester’s work on industrial dynamics and urban dynamics (1961). Cross-impact/structural analysis is a method for assessing the likelihood of events occurring within a forecasted system. These probabilities can be adjusted based on judgments regarding the potential for mutual influence among the events under consideration. In essence, certain events can increase or decrease the likelihood of other events occurring. Many events also trigger cascading developments, whereby one event leads to another, which in turn generates further events, progressively expanding the scope of impacts and influencing subsequent processes. This interdependence among events constitutes the core of cross-impact analysis [Naimi & Pourmohamadi, 2016]. The structural cross-impact analysis method seeks to identify key (explicit or latent) parameters in order to elicit expert opinions and encourage the participation of stakeholders in understanding the complex and often unpredictable behaviors of the system.
In general, structural analysis is conducted in three main stages [Alibeigi et al., 2017]:
The analyses conducted in this study can be broadly divided into two main phases. In the first phase, indicators influencing urban low-carbonization were identified based on a review of previous studies, the characteristics of the study area, and interviews with an expert panel. The indicators included transport infrastructure, travel time and mobility, fuel cost, road network, urban green spaces, compact development, accessibility, land-use mix, travel cost, transport management, electronic transport, macro-level managerial policies, public social awareness, clean fuels, new energy sources, public transport, non-motorized transport, intelligent transport systems, fossil fuels, relocation of factories, and travel time. The expert panel comprised 30 specialists in sustainable urban development studies from the cities of Jolfa and Jananlu, selected through purposive sampling and interviewed accordingly. Specifically, 15 experts were selected and interviewed in each city. The emphasized indicators were extracted through interview transcript coding and subsequently presented to the same expert panel for prioritization. With the consent of the interviewees, the interviews were recorded, transcribed, and prepared for analysis. During transcript review, key factors were identified, and data coding was performed to harmonize overlapping factors. The codes were then manually categorized, without the use of specialized software, and repeatedly reviewed and refined until the principal parameters influencing low-carbonization in Jolfa and Jananlu were determined.
Subsequently, the extracted data were entered into Microsoft Excel, averaged, and then imported into the MICMAC software for analysis. The mean values of expert judgments regarding the parameters influencing low-carbonization were entered into MICMAC in the form of a 21×21 matrix. Based on the MICMAC outputs, the filling index (which reflects the reliability of the questionnaire or data) reached 0.92 after two data rotations, indicating high reliability of the collected data and strong interrelationships among the parameters. Overall, within the 21×21 matrix, a total of 410 evaluated relationships were obtained. Of these, 31 values were zeros (indicating no influence), 41 were ones (weak influence), 78 were twos (moderate influence), and 291 were threes (strong influence), which represented the most frequently occurring category. Additionally, potential parameters without assigned scores (p) were identified. In the final stage, the influential and dependent parameters related to low-carbonization in the study area were identified and analyzed according to their respective priorities.
Findings
Based on their degrees of influence and dependence, the studied parameters were classified into several distinct categories. These categories include input (key) parameters, intermediate parameters, outcome parameters, negligible parameters, and clustered or indeterminate parameters.
The input or key parameters represent the strategic drivers influencing low-carbonization in the cities of Jolfa and Jananlu within the Aras Free Zone. These parameters include electronic transport, intelligent transport systems, and the adoption of low-carbon and renewable energy sources used globally as alternatives to the energy sources currently utilized in the country.
The intermediate parameters are characterized by both high influence and high dependence, making them particularly important for long-term planning in the region. These parameters include fuel cost, transport infrastructure, macro-level managerial decisions, land-use mix, urban compaction, transport management, substitution of fuels such as Euro 2 gasoline instead of Euro 4, fossil fuels, the use of renewable energy with adequate accessibility, public transport culture, non-motorized transport, and the reduction of travel time.
Outcome parameters are those with relatively low influence but high dependence. According to expert assessments, no parameter in this study can be considered purely influential without also being affected by other parameters, as all identified parameters exhibit both influence and dependence.
Negligible parameters are those with low levels of both influence and dependence. These parameters represent relatively stable trends with limited change and are often regarded as independent parameters. Social awareness and urban green spaces fall into this category.
Clustered or indeterminate parameters represent elements with uncertain future behavior from a systems perspective. In this study, types of energy were identified as belonging to this category.
Direct and indirect effects of parameters.
Within this analytical framework, the relationships among parameters were examined not only in their direct form but also through indirect effects, assessed by elevating the interaction matrix to higher powers. The results indicate that macro-level managerial policies, urban infrastructure in various domains, particularly transport infrastructure transport management, the costs associated with new fuels, the adoption of intelligent and electronic transport systems, and road networks exert the strongest direct influence on low-carbonization in the studied cities. In contrast, social awareness and urban green spaces demonstrate comparatively lower levels of direct influence.
Analysis of direct influence relationships reveals that electronic transport, macro-level managerial policies, urban road networks, relocation of factories outside urban areas, and fuel costs exhibit the strongest direct effects. Parameters such as urban compaction, electric fuels, and land-use mix also show strong levels of influence. A key observation from comparing direct and indirect effects is that most parameters identified as influential through indirect pathways are likewise among the most influential in direct interaction analysis. This finding highlights the pivotal role of these parameters as primary driving forces in advancing low-carbonization in the Aras Free Zone.
When examining the degree of dependence among parameters, fuel cost (including conventional and electric fuels), travel time, transport management, infrastructure, and non-motorized transport emerge as the most highly dependent parameters, indicating that their realization is strongly influenced by other factors within the system.
Overall, macro-level managerial policies at national, regional, and urban levels, urban infrastructure, particularly urban transport infrastructure, the adoption of electronic transport technologies, and improvements to intra-urban and inter-urban road networks exhibit the highest levels of influence on achieving low-carbonization in the cities under study.
Discussion
The aim of this study was to identify the parameters influencing the low-carbonization of the cities of Jolfa and Jananlu in the Aras Free Zone in northwestern Iran. Owing to factors such as the presence of extensive transport and communication corridors in its hinterland, its connection to major national road networks, proximity to the Caspian and Black Seas, and the existence of the Jolfa Customs Office as a first-tier national gateway, the Aras Free Zone allocates a substantial share of carbon emissions to the transport sector.
The findings indicate that fuel cost, national transport infrastructure, macro-level managerial decisions, land-use mix, urban compaction, transport management, adoption of new energy types (such as substituting Euro 2 gasoline for Euro 4), reduction of fossil fuel use, utilization of renewable and clean energy sources, adequate accessibility, public transport culture, non-motorized transport, and reduced travel time function as intermediate parameters in the low-carbonization of Jolfa and Jananlu. Although transport development contributes positively to economic growth, it also generates adverse environmental impacts and increases greenhouse gas emissions [Liddle & Lung, 2013]. Consequently, the environmental dimensions of transport development have received growing attention from researchers. The creation and expansion of transport-related infrastructure, particularly the development of public transport and the reduction of reliance on private vehicles, enhance speed and accessibility while simultaneously lowering carbon emissions, reducing transport costs, and exerting positive effects on regional economic growth. Kalantarzadeh et al. [2021] have emphasized the development of transport infrastructure as a key factor in reducing carbon emissions from urban transport. While their study primarily focused on rail and air transport, the present research considers road, rail, and air transport systems. Similarly, Mahdavi et al. [2018] have demonstrated that improving urban infrastructure to exploit urban economies of scale, decentralizing economic activities, and enhancing the quality of public transport systems constitute effective measures for reducing CO₂ emissions in the transport sector. Public transport development can also play a critical role in facilitating mobility and promoting the adoption of low-carbon vehicle technologies. Unlike Mahdavi et al. [2018], who have examined interprovincial differences in CO₂ emissions across Iran, the present study focuses on identifying influential factors and practical strategies for advancing low-carbonization in the cities of Jolfa and Jananlu. The significant contribution of public transport to greenhouse gas reduction, along with its co-benefits, such as reduced traffic congestion and improved air quality has been confirmed in previous studies [Wimbady et al., 2021; Dillman et al., 2021; Liddle & Lung, 2013].
The most critical strategic parameters influencing low-carbonization in Jolfa and Jananlu were identified as the development of transport systems based on modern electronic approaches, intelligent transport systems, and the adoption of standardized and renewable energy sources. In this context, energy supply management aimed at optimizing renewable energy demand systems, alongside controlling fossil fuel consumption in the transport sector and other sectors to reduce CO₂ emissions, represents a policy area requiring particular attention. Fazeli [2014] noted that the use of renewable energy in vehicles can reduce air pollution, mitigate greenhouse gas emissions, and decrease dependence on imported oil. Within this framework, green transport has emerged as a relatively new concept, seeking to establish urban transport systems that are comfortable, safe, efficient, low-pollution, human-centered, and diverse. According to Senin et al. [2021], green transport can be supported through alternative fuels and advanced vehicle technologies, including hybrid electric vehicles, compressed-air vehicles, battery electric vehicles, and hydrogen fuel-cell vehicles. Moreover, the active promotion of green transport contributes to more efficient use of road networks, alleviation of traffic congestion, reduced energy consumption, improved air quality, and the encouragement of healthier lifestyles among urban residents. While Senin et al. [2021] have examined the effects of green transport on low-carbon urban development in Port Dickson, Malaysia, their findings provide valuable insights that may serve as a motivating reference for strengthening related infrastructure and advancing practical policies and strategies for implementation in other contexts.
The development of transport systems through modern electronic approaches leads to savings in time, costs, and human resources, enhances productivity indicators, and ultimately reduces CO₂ emissions both directly and indirectly. In intelligent transport systems (ITS), which integrate information, communication, and control technologies, improvements in network performance are accompanied by reductions in travel delays and enhancements in traffic safety. These outcomes collectively improve quality of life and environmental conditions while contributing to significant carbon reductions. Emphasis on advanced public transport systems, such as monorails and metro systems with consideration of environmental impacts and carbon emission reduction has also been highlighted in previous studies [Abedi et al., 2011; MacIsaac, 2010].
Overall, macro-level managerial policies at national, regional, and urban scales; urban infrastructure in various domains, particularly urban transport; the adoption of electronic transport technologies; and improvements to intra-urban and inter-urban road networks were found to exert the strongest influence on low-carbonization in the studied cities. Given that the volume of interurban transport in the Aras Free Zone significantly exceeds intracity travel in Jolfa and Jananlu, largely due to the region’s economic and geographic characteristics, greater emphasis on interurban transport should be incorporated into planning processes. In addition, street capacity should be designed to accommodate diverse urban needs, with dedicated corridors provided for public transport modes.
Conclusion
The development of the transport system in northwestern Iran has intensified greenhouse gas emissions beyond those generated by natural processes and other human activities. The findings of this study indicate that strategies such as advancing transport systems through modern electronic approaches, implementing intelligent transport systems, adopting standardized and renewable energy sources, and expanding transport infrastructure and intra- and inter-urban road networks are critical and effective drivers of low-carbon urban development in the Aras Free Zone. By pursuing policies that promote green transport and by developing the necessary infrastructure and technologies for electronic transport systems, a low-carbon future for the studied areas can be envisioned.
Moreover, formulating effective strategies to raise public awareness about the importance of air low-carbonization and to encourage citizen participation in the implementation of practical CO₂ reduction measures is essential. Such efforts can facilitate more rapid and effective achievement of low-carbon development goals in the region.
Acknowledgments: There are no acknowledgments to declare.
Ethical Permission: No ethical approval was required for this study.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Moniri F (first author), Introduction Writer/Principal Researcher (30%); Asghari H (second author), Methodologist/Discussion Writer (30%); Poursheikhan A (third author), Assistant Researcher (20%); Hasani-Mehr SS (fourth author), Statistical Analyst (20%).
Funding: This research received no specific grant from any funding agency.
Recently, global climate change resulting from the excessive consumption of fossil energy has attracted increasing attention from the international community [Gokgoz & Guvercin, 2018]. As the principal driver of global climate change, the rapid rise in greenhouse gas (GHG) emissions has not only led to global warming, sea-level rise, and climatic variability, but has also exerted substantial adverse impacts on human health and economic development [Tang et al., 2018; Karlsson & Ziebarth, 2018]. Therefore, reducing GHG emissions and promoting low-carbon economic development are imperative. Cities, as regional or even national hubs, play a significant role in economic, political, cultural, and social development. At the same time, they are major consumers of local resources and primary sources of GHG emissions [Khanna et al., 2014]. Consequently, the key to reducing global GHG emissions lies in cities [Sudmant et al., 2016]. Studies indicate that the majority of energy consumption occurs in urban areas [Kean Fong et al., 2008]. Hosting more than half of the world’s population, cities function as the main centers of economic activity and energy use. Although they occupy only about 2% of the Earth’s surface, they account for approximately 75% of global energy consumption and nearly 80% of GHG emissions [Zheng et al., 2011].
The United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol serve as platforms for collectively addressing this global issue and its impacts. In addition to these two platforms, the Paris Agreement was adopted by the Conference of the Parties to the UNFCCC and approved by consensus in Paris on December 12, 2015. This agreement was the outcome of intensive negotiations that began in Bali in 2007 and lasted for more than eight years. Its overarching objectives include holding the increase in the global average temperature well below 2°C and pursuing efforts to limit the increase to 1.5°C above pre-industrial levels; enhancing adaptive capacity to climate change impacts; strengthening climate resilience; and fostering low-GHG emission development pathways without threatening food production, while aligning financial flows with low-emission and climate-resilient development. The Agreement incorporates the principles of “equity” and “Nationally Determined Contributions (NDCs),” allowing each country to set its own targets according to its capacities while pursuing sustainable development goals. In particular, climate action in this context requires enhanced transfer of scientific knowledge, research, and initiatives, which substantially facilitate the effective implementation of national environmental actions [Sereenonchai et al., 2020].
To combat climate change and achieve sustainable development goals, Low-Carbon Cities (LCCs) have emerged as one of the vital initiatives proposed and implemented globally under the UNFCCC framework. This initiative seeks to reshape human behavior and national economies to reduce dependence on carbon-intensive activities while achieving GHG emission reductions without constraining economic growth. The development of low-carbon cities has thus become an essential global response to the threats posed by climate change [Glaeser & Kahn, 2010; Tan et al., 2017; Fu et al., 2021]. Liu et al. [2017] argue that low-carbon city development is a process of public participation that requires concerted efforts by governments, enterprises, and individuals to reduce carbon emissions. The concept of the low-carbon city constitutes an integral component of sustainable development [Khanna et al., 2014]. Carbon emissions can be effectively reduced through the adoption of low-carbon development measures without undermining urban economic growth.
Although many countries and regions have now prioritized carbon reduction, the concept of the “low-carbon city” remains relatively nascent, and consensus on its definition has yet to be reached [While et al., 2010]. In practice, a low-carbon city provides a sustainability framework, and the theoretical and practical advancement of sustainable development is increasingly achievable through the realization of low-carbon cities. Fundamentally, low-carbon cities are those that implement serious and effective measures to mitigate environmental impacts and emissions. Low-carbon strategies, combining specific urban development objectives with constraints, should be promoted incrementally and in phases. This process requires substantial systemic transformations, including changes in infrastructure, institutions, and user practices [Wimbady et al., 2021].
The transport sector’s dependence on fossil fuels has driven the proliferation of internal combustion engine vehicles over the past century. This, in turn, has stimulated the expansion of infrastructure and low-density urban forms, which have increased private vehicle ownership and carbon dioxide (CO₂) emissions from mobility [Seto et al., 2014]. Meanwhile, many cities worldwide, particularly in Asia and North America still suffer from limited access to public transportation. The Organisation for Economic Co-operation and Development (OECD) estimates that cities with populations exceeding 300,000 accounted for 20% of CO₂ emissions from transport and passenger mobility in 2014 alone [Wimbady et al., 2021]. Statistics indicate that approximately 19% of global energy consumption and more than one quarter of global CO₂ emissions are attributable to transport, with emissions from public transport increasing faster than those from other sectors. Studies by the International Energy Agency (IEA) show that the transport sector is the largest energy consumer [Ebadinia et al., 2016]. Iran also represents a significant share in this sector. According to the Statistical Yearbook (latest edition, 2016), total CO₂ emissions in Iran amounted to 586 million tons in 2015, of which 30% originated from power plants affiliated with the Ministry of Energy, the private sector, and large industries; 25% from transport; 24% from residential, commercial, and public sectors; and 16% from industrial fuel consumption [Statistical Center of Iran, 2016].
Various indicators have been proposed to facilitate the establishment of low-carbon cities. Low-carbon urban development is a complex system encompassing infrastructure, industry, technology, and energy [Wang et al., 2018]. Numerous studies have examined effective approaches to low-carbon city development in specific domains, such as infrastructure strategies and energy consumption [Silver & Marvin, 2017; Ohnishi et al., 2018], as well as financial support mechanisms [Van der Heijden, 2017]. Zhang et al. [2021] have identified factors including available water resources, renewable energy consumption, CO₂ offsetting, nature-based solutions with a focus on process management, reduction of arable land expansion, urban green spaces, waste recycling capacity, CO₂ removal capacity, and urban waste treatment as key determinants of low-carbon city development in China. According to Li et al. [2021], the implementation of low-carbon city initiatives in China is feasible through reductions in energy consumption, upgrading of industrial structures, and advancement of technological innovation. Ahmad Ali et al. [2020] emphasize the reform of energy consumption patterns in the construction sector as a critical factor in reducing urban carbon emissions. Fraker [2013] highlights appropriate urban form, convenient access to public transport, extensive facilities for promoting cycling and walking, and reduced reliance on private vehicles as essential elements for achieving a low-carbon urban future through transport reform.
Factors such as the region’s distinctive geo-economic position; its location along the Silk Road; its role as a commercial crossroads between Europe and Central Asia; the presence of well-developed transport and communication networks in the hinterland and connections to major road networks and the electrified Tabriz–Jolfa railway; proximity to the Caspian and Black Seas; the presence of the Jolfa Customs Office (a first-tier national gateway); industrial estates; border markets; the Saint Stepanos Monastery; and major tourism destinations within the Aras Free Zone collectively underscore the critical importance of the transport sector in the cities of the Aras Free Zone. Given these conditions, high traffic volumes, particularly dependence on private vehicles and limited inclination toward public transport for urban and interurban travel have accentuated the role of transport in CO₂ emissions and air pollution. This highlights the necessity of investigating this issue to better understand the problem and to propose practical strategies for air pollution reduction. Accordingly, Moniri et al. [2022] also have emphasized the role of transport in the Jolfa and Jananlu regions and the importance of examining this factor in the low-carbonization of air quality. In this context, the primary objective of the present study is to analyze the role of transport in achieving low-carbon and carbon-free cities in the Aras Free Zone. Specifically, the study seeks to answer the following question: What are the most influential parameters affecting low-carbonization (with an emphasis on transport) in the Aras Free Zone (the cities of Jolfa and Jananlu)?
Methodology
This study is descriptive–analytical in nature and was conducted in 2021 using the cross-impact analysis method. The spatial scope of the research is the Aras Free Zone. The Aras Free Zone has been planned over an area of approximately 51,000 hectares along the Aras River. It encompasses parts of the counties of Jolfa and Khoda Afarin, located along Iran’s borders with Azerbaijan, Armenia, and Nakhchivan. The Aras Free Zone consists of four independent yet interconnected areas. Its core area, covering 20,500 hectares, is located in Jolfa County, while three detached zones, Qali Beyglu (24,000 ha), Khoda Afarin (6,100 ha), and Norduz (240 ha), collectively form the remaining extent of the Aras Free Zone. With Jolfa as its central city, the Aras Free Zone is situated along the historic Silk Road corridor. According to the latest national population and housing census, the city of Jolfa has a population of 8,810 comprising 2,547 households, while the city of Jananlu has a population of 1,742, including 555 households [Statistical Center of Iran, 2016].
Structural cross-impact analysis is one of the most widely used foresight methods. After adopting a systems-based approach and demonstrating its analytical capacity, it experienced significant development in the late 1960s and was further advanced through Jay Forrester’s work on industrial dynamics and urban dynamics (1961). Cross-impact/structural analysis is a method for assessing the likelihood of events occurring within a forecasted system. These probabilities can be adjusted based on judgments regarding the potential for mutual influence among the events under consideration. In essence, certain events can increase or decrease the likelihood of other events occurring. Many events also trigger cascading developments, whereby one event leads to another, which in turn generates further events, progressively expanding the scope of impacts and influencing subsequent processes. This interdependence among events constitutes the core of cross-impact analysis [Naimi & Pourmohamadi, 2016]. The structural cross-impact analysis method seeks to identify key (explicit or latent) parameters in order to elicit expert opinions and encourage the participation of stakeholders in understanding the complex and often unpredictable behaviors of the system.
In general, structural analysis is conducted in three main stages [Alibeigi et al., 2017]:
- identification and formulation of influential parameters using various approaches such as literature review, environmental scanning, and interviews;
- description of the relationships among parameters, through which a network of interrelations is established; and
- identification of key parameters for scenario development, conducted using the MICMAC software.
The analyses conducted in this study can be broadly divided into two main phases. In the first phase, indicators influencing urban low-carbonization were identified based on a review of previous studies, the characteristics of the study area, and interviews with an expert panel. The indicators included transport infrastructure, travel time and mobility, fuel cost, road network, urban green spaces, compact development, accessibility, land-use mix, travel cost, transport management, electronic transport, macro-level managerial policies, public social awareness, clean fuels, new energy sources, public transport, non-motorized transport, intelligent transport systems, fossil fuels, relocation of factories, and travel time. The expert panel comprised 30 specialists in sustainable urban development studies from the cities of Jolfa and Jananlu, selected through purposive sampling and interviewed accordingly. Specifically, 15 experts were selected and interviewed in each city. The emphasized indicators were extracted through interview transcript coding and subsequently presented to the same expert panel for prioritization. With the consent of the interviewees, the interviews were recorded, transcribed, and prepared for analysis. During transcript review, key factors were identified, and data coding was performed to harmonize overlapping factors. The codes were then manually categorized, without the use of specialized software, and repeatedly reviewed and refined until the principal parameters influencing low-carbonization in Jolfa and Jananlu were determined.
Subsequently, the extracted data were entered into Microsoft Excel, averaged, and then imported into the MICMAC software for analysis. The mean values of expert judgments regarding the parameters influencing low-carbonization were entered into MICMAC in the form of a 21×21 matrix. Based on the MICMAC outputs, the filling index (which reflects the reliability of the questionnaire or data) reached 0.92 after two data rotations, indicating high reliability of the collected data and strong interrelationships among the parameters. Overall, within the 21×21 matrix, a total of 410 evaluated relationships were obtained. Of these, 31 values were zeros (indicating no influence), 41 were ones (weak influence), 78 were twos (moderate influence), and 291 were threes (strong influence), which represented the most frequently occurring category. Additionally, potential parameters without assigned scores (p) were identified. In the final stage, the influential and dependent parameters related to low-carbonization in the study area were identified and analyzed according to their respective priorities.
Findings
Based on their degrees of influence and dependence, the studied parameters were classified into several distinct categories. These categories include input (key) parameters, intermediate parameters, outcome parameters, negligible parameters, and clustered or indeterminate parameters.
The input or key parameters represent the strategic drivers influencing low-carbonization in the cities of Jolfa and Jananlu within the Aras Free Zone. These parameters include electronic transport, intelligent transport systems, and the adoption of low-carbon and renewable energy sources used globally as alternatives to the energy sources currently utilized in the country.
The intermediate parameters are characterized by both high influence and high dependence, making them particularly important for long-term planning in the region. These parameters include fuel cost, transport infrastructure, macro-level managerial decisions, land-use mix, urban compaction, transport management, substitution of fuels such as Euro 2 gasoline instead of Euro 4, fossil fuels, the use of renewable energy with adequate accessibility, public transport culture, non-motorized transport, and the reduction of travel time.
Outcome parameters are those with relatively low influence but high dependence. According to expert assessments, no parameter in this study can be considered purely influential without also being affected by other parameters, as all identified parameters exhibit both influence and dependence.
Negligible parameters are those with low levels of both influence and dependence. These parameters represent relatively stable trends with limited change and are often regarded as independent parameters. Social awareness and urban green spaces fall into this category.
Clustered or indeterminate parameters represent elements with uncertain future behavior from a systems perspective. In this study, types of energy were identified as belonging to this category.
Direct and indirect effects of parameters.
Within this analytical framework, the relationships among parameters were examined not only in their direct form but also through indirect effects, assessed by elevating the interaction matrix to higher powers. The results indicate that macro-level managerial policies, urban infrastructure in various domains, particularly transport infrastructure transport management, the costs associated with new fuels, the adoption of intelligent and electronic transport systems, and road networks exert the strongest direct influence on low-carbonization in the studied cities. In contrast, social awareness and urban green spaces demonstrate comparatively lower levels of direct influence.
Analysis of direct influence relationships reveals that electronic transport, macro-level managerial policies, urban road networks, relocation of factories outside urban areas, and fuel costs exhibit the strongest direct effects. Parameters such as urban compaction, electric fuels, and land-use mix also show strong levels of influence. A key observation from comparing direct and indirect effects is that most parameters identified as influential through indirect pathways are likewise among the most influential in direct interaction analysis. This finding highlights the pivotal role of these parameters as primary driving forces in advancing low-carbonization in the Aras Free Zone.
When examining the degree of dependence among parameters, fuel cost (including conventional and electric fuels), travel time, transport management, infrastructure, and non-motorized transport emerge as the most highly dependent parameters, indicating that their realization is strongly influenced by other factors within the system.
Overall, macro-level managerial policies at national, regional, and urban levels, urban infrastructure, particularly urban transport infrastructure, the adoption of electronic transport technologies, and improvements to intra-urban and inter-urban road networks exhibit the highest levels of influence on achieving low-carbonization in the cities under study.
Discussion
The aim of this study was to identify the parameters influencing the low-carbonization of the cities of Jolfa and Jananlu in the Aras Free Zone in northwestern Iran. Owing to factors such as the presence of extensive transport and communication corridors in its hinterland, its connection to major national road networks, proximity to the Caspian and Black Seas, and the existence of the Jolfa Customs Office as a first-tier national gateway, the Aras Free Zone allocates a substantial share of carbon emissions to the transport sector.
The findings indicate that fuel cost, national transport infrastructure, macro-level managerial decisions, land-use mix, urban compaction, transport management, adoption of new energy types (such as substituting Euro 2 gasoline for Euro 4), reduction of fossil fuel use, utilization of renewable and clean energy sources, adequate accessibility, public transport culture, non-motorized transport, and reduced travel time function as intermediate parameters in the low-carbonization of Jolfa and Jananlu. Although transport development contributes positively to economic growth, it also generates adverse environmental impacts and increases greenhouse gas emissions [Liddle & Lung, 2013]. Consequently, the environmental dimensions of transport development have received growing attention from researchers. The creation and expansion of transport-related infrastructure, particularly the development of public transport and the reduction of reliance on private vehicles, enhance speed and accessibility while simultaneously lowering carbon emissions, reducing transport costs, and exerting positive effects on regional economic growth. Kalantarzadeh et al. [2021] have emphasized the development of transport infrastructure as a key factor in reducing carbon emissions from urban transport. While their study primarily focused on rail and air transport, the present research considers road, rail, and air transport systems. Similarly, Mahdavi et al. [2018] have demonstrated that improving urban infrastructure to exploit urban economies of scale, decentralizing economic activities, and enhancing the quality of public transport systems constitute effective measures for reducing CO₂ emissions in the transport sector. Public transport development can also play a critical role in facilitating mobility and promoting the adoption of low-carbon vehicle technologies. Unlike Mahdavi et al. [2018], who have examined interprovincial differences in CO₂ emissions across Iran, the present study focuses on identifying influential factors and practical strategies for advancing low-carbonization in the cities of Jolfa and Jananlu. The significant contribution of public transport to greenhouse gas reduction, along with its co-benefits, such as reduced traffic congestion and improved air quality has been confirmed in previous studies [Wimbady et al., 2021; Dillman et al., 2021; Liddle & Lung, 2013].
The most critical strategic parameters influencing low-carbonization in Jolfa and Jananlu were identified as the development of transport systems based on modern electronic approaches, intelligent transport systems, and the adoption of standardized and renewable energy sources. In this context, energy supply management aimed at optimizing renewable energy demand systems, alongside controlling fossil fuel consumption in the transport sector and other sectors to reduce CO₂ emissions, represents a policy area requiring particular attention. Fazeli [2014] noted that the use of renewable energy in vehicles can reduce air pollution, mitigate greenhouse gas emissions, and decrease dependence on imported oil. Within this framework, green transport has emerged as a relatively new concept, seeking to establish urban transport systems that are comfortable, safe, efficient, low-pollution, human-centered, and diverse. According to Senin et al. [2021], green transport can be supported through alternative fuels and advanced vehicle technologies, including hybrid electric vehicles, compressed-air vehicles, battery electric vehicles, and hydrogen fuel-cell vehicles. Moreover, the active promotion of green transport contributes to more efficient use of road networks, alleviation of traffic congestion, reduced energy consumption, improved air quality, and the encouragement of healthier lifestyles among urban residents. While Senin et al. [2021] have examined the effects of green transport on low-carbon urban development in Port Dickson, Malaysia, their findings provide valuable insights that may serve as a motivating reference for strengthening related infrastructure and advancing practical policies and strategies for implementation in other contexts.
The development of transport systems through modern electronic approaches leads to savings in time, costs, and human resources, enhances productivity indicators, and ultimately reduces CO₂ emissions both directly and indirectly. In intelligent transport systems (ITS), which integrate information, communication, and control technologies, improvements in network performance are accompanied by reductions in travel delays and enhancements in traffic safety. These outcomes collectively improve quality of life and environmental conditions while contributing to significant carbon reductions. Emphasis on advanced public transport systems, such as monorails and metro systems with consideration of environmental impacts and carbon emission reduction has also been highlighted in previous studies [Abedi et al., 2011; MacIsaac, 2010].
Overall, macro-level managerial policies at national, regional, and urban scales; urban infrastructure in various domains, particularly urban transport; the adoption of electronic transport technologies; and improvements to intra-urban and inter-urban road networks were found to exert the strongest influence on low-carbonization in the studied cities. Given that the volume of interurban transport in the Aras Free Zone significantly exceeds intracity travel in Jolfa and Jananlu, largely due to the region’s economic and geographic characteristics, greater emphasis on interurban transport should be incorporated into planning processes. In addition, street capacity should be designed to accommodate diverse urban needs, with dedicated corridors provided for public transport modes.
Conclusion
The development of the transport system in northwestern Iran has intensified greenhouse gas emissions beyond those generated by natural processes and other human activities. The findings of this study indicate that strategies such as advancing transport systems through modern electronic approaches, implementing intelligent transport systems, adopting standardized and renewable energy sources, and expanding transport infrastructure and intra- and inter-urban road networks are critical and effective drivers of low-carbon urban development in the Aras Free Zone. By pursuing policies that promote green transport and by developing the necessary infrastructure and technologies for electronic transport systems, a low-carbon future for the studied areas can be envisioned.
Moreover, formulating effective strategies to raise public awareness about the importance of air low-carbonization and to encourage citizen participation in the implementation of practical CO₂ reduction measures is essential. Such efforts can facilitate more rapid and effective achievement of low-carbon development goals in the region.
Acknowledgments: There are no acknowledgments to declare.
Ethical Permission: No ethical approval was required for this study.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Moniri F (first author), Introduction Writer/Principal Researcher (30%); Asghari H (second author), Methodologist/Discussion Writer (30%); Poursheikhan A (third author), Assistant Researcher (20%); Hasani-Mehr SS (fourth author), Statistical Analyst (20%).
Funding: This research received no specific grant from any funding agency.
Keywords:
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