Analysis of Decarbonization Potential in Mobility Sector with High Spatial Resolution: Study Case of the Metropolitan Area of Valencia (Spain)

Abstract

This study addresses the urgent need for sustainable urban mobility through a comprehensive analysis of decarbonization potential in the metropolitan area of Valencia, Spain. The research is motivated by the imperative to mitigate climate change amidst high traffic and congestion levels. Utilizing the Origin–Destination matrix from the Valencian community’s mobility plan, the study prioritizes displacements for substitution by sustainable alternatives. Through a detailed case study analysis, critical areas for decarbonization are identified, and practical strategies to reduce carbon emissions are proposed. The methodology encompasses a thorough literature review on decarbonization measures, examination of existing plans, and analysis of sustainable trips with high spatial resolution using geographic information systems (GISs). The study identifies trips with significant decarbonization potential and assesses the current public transportation network. Spatial analyses illustrate demand patterns for sustainable transport options, emphasizing the need for tailored strategies. Key findings highlight the role of private and commercial transport in CO₂ emissions, advocating for targeted interventions to enhance active transport infrastructure, promote carpooling, adopt low-emission vehicles, and improve public transport accessibility and efficiency.

1. Introduction

In 2017, the transport sector accounted for 27% of total greenhouse gas emissions in the European Union [1]. Valencia’s Sustainable Climate and Energy Action Plan states that over 50% of CO₂ emissions come from private and commercial transportation [2]. Highlighting the significance of this study, the Basic Mobility Plan of the metropolitan area of Valencia revealed that 40% of trips in the community are concentrated in the metropolitan area, with only 13% using public transportation compared to 41% opting for private cars [3]. Integrating theory and practice aims to propose practical measures for carbon emission reduction in transportation.

Drawing insights from prominent works on sustainable urban mobility that have seen significant advancements [4], a literature review identifies a critical gap concerning the metropolitan area of Valencia—the absence of localized, high-resolution strategies for identifying and prioritizing displacements with high decarbonization potential [5]. Previous authors [6] offer valuable insights into broader considerations of sustainable mobility; however, addressing the specific needs of the València metropolitan area remains an ongoing challenge.

M.R. Zamora Roselló [7] address this gap by analyzing the mobility sector and its relevance to the healthcare sector. This includes analyzing public transportation accessibility through GTFS [8] and using open data to underscore the importance of these aspects [9]. These references, along with others mentioned earlier, lay the groundwork for a localized and context-specific approach to sustainable urban mobility in the València metropolitan area.

Recent studies have shown significant advancements in the field of sustainable urban transportation, particularly in the areas of electrification and smart mobility technologies. For instance, the adoption of electric vehicles (EVs) has been a major focus, with studies highlighting the impact of EVs on reducing urban emissions [10,11]. Additionally, the development of smart grid infrastructures to support EV charging has been documented as a critical factor in enhancing the feasibility and efficiency of electric mobility [12].

Furthermore, the implementation of intelligent transportation systems (ITSs) has demonstrated substantial improvements in traffic management and energy efficiency. Recent research indicates that ITSs can significantly reduce congestion and emissions by optimizing traffic flow and providing real-time information to commuters [13]. These technologies enable more efficient use of existing transportation networks, thereby contributing to sustainability goals [14].

In the realm of policy, the European Green Deal has set ambitious targets for reducing greenhouse gas emissions and promoting sustainable urban mobility. Recent policy analyses have explored the implications of these targets for urban transportation systems across Europe [15,16]. National policies, influenced by the Green Deal, are being implemented to enhance public transportation, expand cycling infrastructure, and support the transition to electric mobility [17].

Studies from countries like Germany and the Netherlands provide valuable insights into the effectiveness of these policies. For example, Germany’s National Platform for the Future of Mobility has outlined comprehensive strategies to integrate various modes of transport and promote sustainable urban mobility [18]. These policies serve as models for other regions aiming to achieve similar sustainability goals, demonstrating that well-designed policy frameworks can significantly drive urban transportation toward sustainability [19].

Despite the substantial body of research on sustainable urban transportation, several critical gaps remain unaddressed. First, while numerous studies have focused on the potential of electric vehicles (EVs) and intelligent transportation systems (ITSs) to reduce emissions, there is a lack of high-resolution spatial analyses that evaluate the decarbonization potential at the metropolitan level. Most existing studies employ broader geographic scopes or aggregated data, which may overlook local variations in transportation patterns and emission sources [19,20].

Second, there is limited research on the integration of various sustainable transportation technologies and policy frameworks within a single metropolitan area. Previous studies often analyzed individual elements, such as EV adoption or ITS implementation, without considering how these elements interact within a comprehensive urban transportation system [21]. This piecemeal approach can result in suboptimal strategies that fail to maximize the potential benefits of combining different technologies and policies.

Third, the existing literature frequently lacks a robust methodological framework for assessing the practical implications of sustainable transportation policies for urban planners and policymakers. Many studies provide theoretical models or simulations but do not connect these findings to actionable insights that can guide decision-making processes in real-world urban environments [22].

This study employs a high spatial resolution analysis to assess decarbonization potential. This approach was chosen to capture detailed variations in mobility patterns and emissions, which is crucial for identifying specific areas where decarbonization efforts can be most effective. Unlike broader analyses, high-resolution spatial analysis allows for more targeted and precise policy interventions.

2. Materials and Methods

Spatial analysis was conducted using GIS tools, specifically ArcGIS Pro (version 3.0.2), for network analysis and spatial queries. The choice of these tools was based on their capability to handle high-resolution data and provide accurate results. The Origin–Destination matrix was employed to map and analyze mobility patterns, following a rigorous quality control protocol. This method was validated through comparison with secondary datasets, ensuring the reliability and validity of the results obtained [12].

2.1. Data Collection on Decarbonization Measures in the Mobility Sector and Relevant Plans

An extensive literature review and consultation of diverse information sources were undertaken to achieve this study’s primary objective. Emphasis was placed on the foundational resource of Doganiero, G. [4], who provided a holistic overview of decarbonization measures.

Critical mobility plans to influence Valencia, including the Sustainable Urban Mobility Plan (PMUS) [3], Metropolitan Mobility Plan (PMoMe) [23], and impending legislation under the Recovery, Transformation, and Resilience Plan (PRTR) [24], were meticulously examined. A near-comprehensive literature review gathered global insights into decarbonization measures, resulting in a detailed table presenting specific measures and their associated percentage reductions in emissions [25].

2.2. Analysis of Sustainable Displacements in Valencia

GIS tools, particularly ArcGIS Pro, were utilized for spatial analysis. The spatial data were processed and analyzed using rigorous quality control protocols to ensure accuracy. Key GIS functionalities included network analysis and spatial queries, which were validated through comparison with secondary data sources to confirm the reliability of the findings.

2.2.1. City Conditions for Sustainable Travel

An in-depth analysis of Valencia’s environmental suitability for sustainable displacements, such as cycling, electric scooters, and walking, utilized climate data from NOAA [26] and topographic data from IGN [27].

2.2.2. Cycling Infrastructure Evaluation

The assessment of existing cycling infrastructure utilized data from Valencia’s open data portal [28] and IGN [27] for accessibility, safety, and proximity to key destinations.

Parking Facility Analysis: Evaluation of private and shared bicycle parking using datasets from Valencia’s open data portal and entities like Valenbisi and Mibisi [28]. ArcGIS was employed for spatial analysis, presenting bike loans and returns using bivariate color schemes.

2.2.3. Carpooling Analysis

This section examines carpooling initiatives in Valencia, drawing insights from existing research and quantifying the impact of daily car-sharing on CO₂ emission reduction [4].

2.2.4. Private Travel in Electric, Hydrogen, Hybrid, or Natural Gas Vehicles

Insights from the Directorate General of Traffic (DGT) [29] were gathered on “Zero Emissions” and “Eco” vehicles, along with an analysis of charging infrastructure for electric, hydrogen, hybrid, or natural gas vehicles [30].

2.2.5. Public Transport Network Analysis

The public transport network analysis began with obtaining General Transit Feed Specification (GTFS) [8] data from various sources, including the Ministry of Transport, Mobility, and Urban Agenda of Spain’s website [31]. These data, covering services like EMT, MetroValencia, CercaniasRenfe, and MetroBus, were processed using ArcGIS Pro, which is known for its transportation data capabilities [32]. A meticulous verification of essential GTFS files was conducted to ensure reliability, correcting any inconsistencies.

Creating a network involved adding crucial fields to the street shapefile using ArcGIS Pro’s public transport template. Public transport stops are not directly connected to street axes, leading to fictitious stops attached to streets—an intricate network structure vital for a comprehensive accessibility analysis.

The subsequent network analysis assesses accessibility from each service area to stops within a 5 min walking distance, categorizing accessibility based on specified intervals of trips per hour, from none to very high [33]. This nuanced approach offers a detailed understanding of the accessibility landscape.

The resulting service areas intersect with Valencia’s neighborhood and metropolitan municipalities, enabling a breakdown of accessibility statistics by neighborhood and municipality.

The statistical analysis adds depth to aggregate key metrics like minimum, maximum, and mean trips per hour, including dissolving operations. Detailed tables provide a comprehensive overview of accessibility with frequencies for each neighborhood and municipality.

The final step involves the high-resolution representation and analysis of accessibility and frequency categories for each public transport service, enhancing the communicative power of the analysis. This ensures that stakeholders understand the distribution of accessibility across the study area, considering both 5 min walking distances and frequency evaluations.

2.3. Identifying High Decarbonization Potential through OD Matrix

Collaborative analysis of the OD matrix involved categorization based on distance intervals and the application of emission coefficients to each transportation mode, providing valuable insights for sustainable mobility planning in Valencia [34].

The Origin–Destination (OD) matrix used in this study was sourced from the Valencian community’s mobility plan, which is based on comprehensive traffic surveys and data collection. To ensure data reliability, the matrix was cross-verified with secondary traffic data and subjected to expert review. The validation process confirmed the accuracy and representativeness of the data.

2.4. Cross-Analysis for Enhancing Sustainable Mobility

This section leverages insights from previous research to conduct a cross-analysis, generating bivariate maps that unveil relationships between variables related to public transportation accessibility, commuting patterns, emissions, and spatial distribution.

2.5. Sensitivity Analysis of Potential Improvements and Evaluation of Results

Finally, findings from the entire analysis process were synthesized, involving the application of emission reduction percentages to calculate emissions for Valencia and its municipalities (see Figure 1). The outcome was a new, high-resolution representation of emissions, visually representing the estimated emissions with the OD matrix alongside the projected effects of implemented measures over time.

While the high spatial resolution of our data offers detailed insights, it is important to acknowledge some limitations. Data accuracy can be affected by the resolution of input datasets, such as traffic volume estimates and transit schedules. Furthermore, the Origin–Destination matrices used may not fully capture real-time fluctuations in travel patterns, which could introduce some level of bias.

3. Results

The high spatial resolution of our analysis revealed granular patterns in mobility and emissions, offering insights that broader analyses might miss. This level of detail is crucial for developing targeted strategies for reducing carbon emissions and optimizing urban transportation infrastructure.

3.1. Existing Information on Decarbonization Measures and Plans

The findings offer a detailed examination of decarbonization initiatives and strategies to enhance mobility in the Valencia metropolitan area. Strategic directions and critical recommendations from PMoMe, PMUS, PRTR, and the Sustainable Mobility Law collectively emphasize a multifaceted approach to promoting sustainable mobility. Prioritizing non-motorized options, improving public transport, and fostering intermodally [3] underscore a commitment to alternative and environmentally friendly transportation modes.

Implementing a metropolitan cycling network, restructuring the bus network, and enhancing rail network accessibility [23] reveals a coordinated effort to improve existing infrastructure. These actions align with global trends advocating for sustainable and integrated mobility solutions.

Insights from various cities’ experiences with operational and demand-side measures enrich the discussion. Cases like Shenzen [35] and Santiago de Chile [36] highlight the positive impact of traffic light coordination on emission reduction. Regulatory restrictions on car use, exemplified by creating exclusive lanes in Santiago de Chile, demonstrate significant pollution reduction.

Incorporating measures from diverse cities, especially those related to electrifying bus fleets, contributes to a global perspective [37]. The comparison between electric and diesel buses in Macao highlights the potential environmental benefits of transitioning to electric vehicles, emphasizing the necessity for cleaner and more sustainable public transportation options.

Table 1. Measures with their percentage of emission reduction.

Emission Type	System	Bus Rapid Transit (BRT)	Improved Bus Service	Electrification of Bus Fleet
CO2	%	22.4	40	10
CO	%	37.5	-	-
PM	%	6.7	-	40
NOx	%	15.1	-	80

summarizes the results extracted in a collaborative work with the research group ETRAI+D, showcasing percentage reductions in emissions for each operational and demand-side measure. Bus Rapid Transit (BRT) is a highly impactful measure, indicating substantial decreases across multiple pollutants and fuel consumption [38]. These findings suggest that BRT systems can significantly mitigate greenhouse gas emissions and enhance air quality [39].

By synthesizing local and global measures, a foundation is laid for evaluating the feasibility and effectiveness of diverse decarbonization strategies in the Valencia metropolitan area. Positive outcomes observed in various cities underscore the potential success of implementing similar measures, guiding future policy decisions toward achieving a sustainable, low-carbon, urban transport system.

3.2. Analysis of Sustainable Displacements in Valencia

3.2.1. City Conditions for Sustainable Journeys

The analysis of Valencia’s climatic and topographic conditions affirms the suitability for sustainable journeys using active mobility modes. The well-structured network for functional mobility efficiently covers the entire study area, emphasizing the city’s commitment to facilitating sustainable transportation.

3.2.2. Cycling Infrastructure Evaluation

While the road network supports active mobility, evaluating bicycle and electric scooter parking exposes a critical gap between supply and demand. The discrepancy between the existing 9970 parking stations and the estimated 75,114 daily trips [28] necessitates an urgent need for increased and improved parking facilities to encourage decarbonization.

Analyzing the Valenbisi public bicycle service reveals high usage patterns in specific neighborhoods. However, the absence of stations in certain areas emphasizes the need for strategic expansion to underserved neighborhoods.

Hotspots and statistical data extracted from the analysis provide detailed insights into usage patterns, allowing for targeted improvements. Challenges, such as imbalances in demand and availability during specific time frames, as in Figure 2, underscore the importance of data-driven interventions.

The results recognize the significance of open data in conducting a thorough analysis. Commitment to interoperability among bike rental companies is a positive step toward enhancing the overall biking experience and promoting active mobility across the metropolitan area.

The challenge of imbalances between demand and supply necessitates a targeted strategy for reinforcing high-demand neighborhoods and expanding services to areas with limited coverage. Strengthening the Valenbisi service in neighborhoods lacking stations is crucial for reducing carbon emissions. The analysis calls for a comprehensive strategy to promote sustainable journeys in Valencia, emphasizing improving parking infrastructure, expanding public bicycle services, and addressing service disparities to foster active and decarbonized transportation. Data-driven decision-making and efforts toward interoperability are crucial for success.

3.2.3. Carpooling Analysis

Limited awareness of carpooling services is a significant hurdle in Valencia, demanding enhanced visibility measures. Effective strategies involve active promotion by companies, applications, and the Valencia City Council. Learning from the success of the Paterna Technology Park campaign [40] and encouraging companies and applications related to carpooling for online visibility is vital. The city council should leverage its channels and collaborate with existing platforms.

By improving visibility, citizens gain more accessible access to this sustainable commuting option, contributing to emission reduction. Collaborative efforts between the city council and carpooling platforms can establish a more sustainable and interconnected urban mobility system [41].

3.2.4. Private Travel in Electric, Hydrogen, Hybrid, or Natural Gas Vehicles

The current number of gas stations and electric charging points in the province of Valencia is insufficient to meet the demand for private vehicles using sustainable technologies. With 13 gas stations and 64 electric charging points identified, falling short of the needs of over 50,000 cars, substantial improvement in charging infrastructure is necessary.

Enhancing and expanding the charging point network is crucial to promote sustainable vehicles. This initiative, part of the Moves III plan, aims to drive vehicle fleet renewal in the city, significantly impacting the emission reduction [42].

3.2.5. Public Transport Network Analysis

Central neighborhoods exhibit high accessibility to public transport, whereas suburban areas show varied levels, emphasizing the need for targeted improvements (see Figure 3). This underscores the importance of decentralized transportation planning to address specific neighborhood disparities. The results by municipalities highlight the transportation landscape beyond Valencia. Some municipalities boast high accessibility, while others, like Canet d’En Berenguer and Domeño, lack adequate options (see Figure 3). These disparities emphasize the necessity for a comprehensive strategy.

Critical implications and recommendations:

• Decentralized accessibility: Suburban disparities necessitate decentralized transportation planning for precise solutions.
• Municipal strategies: Tailored strategies for municipalities lacking accessibility are crucial for practical improvements.
• Sustainable mobility promotion: Initiatives promoting alternative transportation are vital for overall decarbonization efforts.
• Infrastructure investment: Targeted investments, expanded routes, and improved frequency enhance the public transportation network.

These findings provide insights into the current state and offer a strategic advantage. The analysis allows for pinpointing specific zones that require precise improvements, enabling more effective and accurate interventions to enhance overall transportation accessibility in Valencia. The implementation of these strategies will fortify Valencia’s commitment to sustainable urban mobility, significantly contributing to broader decarbonization objectives.

3.3. Displacements with High Decarbonization Potential

Emissions data across various Valencia neighborhoods showcase notable variations in carbon dioxide (CO₂), nitrogen oxides (NOx), and particulate matter (PM). “Arrancapins” stands out with elevated CO₂ and NOx emissions, while “El Calvari” and “Les Tendetes” demonstrate comparatively lower emissions.

It is essential to consider factors like population density, industrial activities, and traffic intensity influencing these variations. Further investigation is warranted to pinpoint specific sources contributing to emissions in each neighborhood.

Examining emissions data for municipalities surrounding Valencia offers a broader perspective on the overall environmental impact. “Valencia,” “Paterna,” and “Sagunto/Sagunt” significantly contribute to CO₂, NOx, and PM emissions, given their industrialization and higher population density.

These data underscore the need for targeted environmental policies and initiatives at the municipal level to address and mitigate emission sources. Sustainable urban planning and promoting eco-friendly practices become crucial for reducing these municipalities’ ecological footprints.

Analyzing the proportion of private and public transportation in various neighborhood and municipalities provides insights into the city’s mobility patterns. Key observations include the following:

• The neighborhood “Aiora” exhibits a high proportion of private transportation, signaling a potential area for interventions promoting public transit usage.
• Municipalities like “Paterna” and “Torrent” heavily rely on private transportation, emphasizing the importance of enhancing public transport infrastructure in these areas.
• The “Ciutat de les Arts I de les Ciencies” neighborhood showcases a balanced proportion of private and public transportation, indicating a positive trend in sustainable mobility.

Strategic efforts should improve public transportation services, raise awareness about sustainable commuting options, and implement policies incentivizing eco-friendly transportation modes to maximize the city’s decarbonization potential.

3.4. Enhancements for Sustainable Mobility: Analytical Crossroads

3.4.1. Accessibility and Public-Private Transport Proportion

The analysis establishes a direct correlation between limited public transport accessibility and increased private vehicle usage, notably in neighborhoods. Blue polygons highlight areas with insufficient accessibility and high reliance on personal vehicles. Municipalities exhibit a similar pattern, but less prominently, due to concentrated trips in Valencia.

3.4.2. Accessibility and Emission Relationships

Visualizing accessibility intersections with emissions (CO₂, CO, NOx, PM) in neighborhoods emphasizes critical areas. The analysis reveals a compelling relationship between public transportation accessibility and CO₂ emissions in Valencia’s neighborhoods, as depicted in Figure 4. The prominence of this visual representation underscores critical intersections, where blue polygons highlight the correlation between low accessibility and heightened emissions. This emphasizes the urgent need for targeted interventions in these specific areas.

The proposed measures’ critical areas on our network dataset:

• Implementation of Bus Rapid Transit (BRT):

  o

  High-capacity public transport system with swift routes, strategic stops, and traffic priority.

• Upgrade of the existing bus services:

  o

  Optimization of routes and schedules.

  o

  Increased bus frequency.

  o

  Implementation of real-time information systems.

  o

  Enhancement of comfort and safety conditions for passengers.

• Electrification of the bus fleet:

  o

  Replacement of conventional buses with electric or low-emission alternatives.

  o

  Significantly reduces transportation emissions, improving air quality and reducing carbon footprint.

The proposed measures aim to enhance public transport accessibility, diminish private vehicle usage, and ultimately curtail emissions in the metropolitan area.

3.5. Sensitivity Analysis of Potential Improvements and Evaluation of Results

After universally considering homogeneous-reduction emission tendences in emissions tables for neighborhoods and municipalities, the results demonstrate emissions within the exact interval for current and post-implementation scenarios of the proposed measures. The fundamental importance of enhancing public transportation emerges as an effective strategy for emission reduction and promoting sustainable mobility.

The results underscore the pivotal role of public transport in emission reduction by providing a sustainable alternative to highly polluting private vehicles. This significantly decreases greenhouse gas emissions and atmospheric pollutants (Figure 5), improving air quality and climate change mitigation.

4. Discussion

This in-depth study has illuminated intricate connections between accessibility, transportation modes, and emissions in the metropolitan area, providing nuanced insights into challenges and opportunities for sustainable transportation and emission reduction.

Bivariate maps underscore a direct link between limited public transport accessibility and heightened private vehicle usage, notably in neighborhoods. While municipalities exhibit a similar trend, their prominence is mitigated by trips concentrating on Valencia’s central city. The critical need to fortify public transportation emerges, with proposed measures addressing accessibility challenges and assessing their specific impact on emission reduction.

Sensitivity Analyses illustrate the potential environmental benefits of the proposed measures, showcasing reductions in CO₂, NOx, and PM emissions. The unique aspect of the geolocated results allows for precise interventions in specific problem areas.

This study underscores the pivotal role of efficient public transportation in emission reduction, promoting sustainable mobility and mitigating pollutants. The proposed measures emphasize the importance of targeted improvements and align with global sustainability efforts. Continuous efforts to enhance public transport are crucial for sustained emission reduction and sustainable mobility.

Future research should delve into detailed assessments that consider neighborhood and municipality characteristics. Real-world, post-implementation data collection, enriched by geolocated insights, will offer precise evaluations. The study’s policy implications stress the necessity of investing in an accessible and sustainable public transportation system. The proposed measures align with global efforts towards eco-friendly urban transport networks.

This study identifies current challenges and offers tangible, geolocated solutions for sustainable transportation and emission reduction. The findings, enriched by precise geolocated data, serve as a robust foundation for informed policymaking, guiding efforts towards creating more sustainable and resilient urban transport infrastructure.

The use of high spatial resolution analyses has proven valuable in this study by providing detailed insights into local mobility patterns and emissions. This approach not only enhances the accuracy of our findings but also supports the development of more effective and targeted decarbonization strategies. Future research should continue to explore high-resolution methods to address urban mobility challenges.

Our study focuses on urban areas with high traffic densities, which may not fully represent the transportation dynamics in suburban or rural regions. This geographic focus could introduce a bias in the generalizability of our findings to less densely populated areas where transportation patterns and decarbonization potentials may differ.

The limitations related to data accuracy and geographic focus should be considered when interpreting the results. While our findings provide valuable insights for high-density urban areas, the potential biases introduced by the data limitations suggest that additional research in diverse geographic settings and with updated datasets could enhance the robustness of the conclusions.

To address the limitations identified in this study, future research could incorporate more granular data sources and extend the geographic scope to include suburban and rural areas. This would provide a more comprehensive understanding of transportation decarbonization potentials and help validate the findings across different contexts.

This study has clearly documented the assumptions used in the analysis, such as traffic distribution and emissions, and discussed how these assumptions might influence the results. These assumptions are based on theoretical models and empirical data and have been carefully considered to minimize their impact on the interpretation of the findings. This provides a rigorous and transparent context for our conclusions.

Based on our findings, policymakers should consider the implementation of low-emission zones in high-traffic areas identified in the study. Additionally, investing in public transit infrastructure and incentivizing the adoption of electric vehicles could effectively reduce carbon emissions. Our results suggest that targeted investments in these areas could yield significant environmental and social benefits.

Urban planners can leverage our findings to enhance the connectivity between various transportation modes, ensuring a seamless transition from private vehicles to public transport and non-motorized options. This approach not only addresses emission reduction but also improves overall urban mobility and quality of life.