External Transport Costs and Implications for Sustainable Transport Policy

Abstract

This study investigated the external costs of different transport modes and their implications for sustainable transport policy. Utilising the INCONE60 Cargo Flow Model, we quantified and compared road and maritime transport’s environmental and health impacts within European logistics networks. Our findings revealed that road transport incurred external costs up to four times higher than sea transport due to greater emissions and health-related impacts. By implementing strategic modal shifts and optimising routes, we demonstrated the potential to reduce external costs by up to 80%. These results underscore the importance of integrating external costs into decision-making processes, aligning with global sustainability goals, and providing actionable insights for policymakers to promote sustainable practices in global trade.

1. Introduction

Accelerating globalisation and increasing freight volumes have amplified concerns over external transport costs in supply chain management and environmental policy. Optimising global trade supply chains necessitates not only economic efficiency but also the consideration of environmental and social impacts. The transport sector significantly contributes to CO₂ emissions, noise pollution, and other environmental burdens, critical issues in achieving sustainability goals.

Sea transport dominates international trade, whereas road transport is prevalent in intracontinental logistics. This reliance underscores the need to quantify and mitigate external costs, including emissions, congestion, and health impacts. Traditional supply chain management often overlooks these broader effects, leading to incompatibilities between economic activities and environmental sustainability objectives.

Modal shift, the process of transferring freight from road transport to other environmentally friendly modes such as rail or sea transport, has been a crucial topic in transport policy for over two decades. Studies have consistently underscored its significance in reducing external costs, particularly emissions. According to Raza et al. [1], the modal shift from road haulage to short-sea shipping (SSS) is frequently cited as a method to address environmental externalities like air pollution and congestion. Beil and Putz [2] also argue that increasing multimodal transport can significantly reduce freight transport’s negative impact by improving intermodal services’ efficiency. These studies highlight the lower external costs of sea and rail transport modes and the transformative potential of multimodal transport, offering a hopeful vision of a more sustainable industry for long-distance freight.

The European Union’s White Paper on Transport has set clear targets to shift 30% of road freight over 300 km to rail or waterborne transport by 2030 and over 50% by 2050 (Beil and Putz [2], Pinchasik, et al. [3]). However, despite these policies, road transport continues to dominate, particularly for distances under 300 km, as Pinchasik et al. highlighted. Road transport offers flexibility and incurs fewer operational costs for shorter distances.

Despite the environmental benefits, the adoption of modal shift strategies remains limited. A recurring challenge is the higher cost and lower flexibility of rail and waterborne transport compared to road transport (Grzelakowski [4], Raza et al. [1]). Grzelakowski points out that regulatory frameworks designed to internalise the external costs of road transport are often insufficient, highlighting the urgent need for policy changes to incentivise widespread modal shifts. Furthermore, Pfoser S. [5] identifies barriers such as infrastructure inadequacies, lack of policy harmonisation, and operational inefficiencies that prevent the full realisation of multimodal transport’s potential.

In Sweden, for example, Björk et al. [6] argue that even though modal shift policies have been promoted as part of the climate agenda, road freight transport continues to expand due to advancements in vehicle technology and road infrastructure. The failure to achieve significant modal shifts in countries like Italy (Simonelli et al. [7]) is also attributed to insufficient financial incentives for non-road modes, which struggle to compete with road transport’s cost-effectiveness.

Research has shown that well-designed incentive mechanisms can enhance the attractiveness of eco-friendly transport modes. Simonelli et al. [7] propose a region-based scheme that optimises incentives according to specific origin-destination pairs, making non-road transport modes more competitive. This approach aligns with earlier suggestions by Pinchasik et al., who advocate for harmonised policies across borders to increase the effectiveness of modal shift strategies in the Nordic region.

Meanwhile, the Eslamipoor and Sepehriar [8] study on centralised green supply chains highlights how circular economy principles can further reduce emissions through efficient transport and supply chain coordination. This study demonstrates the potential of integrating modal shifts within broader supply chain innovations to enhance environmental and economic performance.

Understanding the economic impacts of external cost internalisation and exploring alternative fuel technologies for road freight may complement efforts to shift freight to greener modes (Björk et al. [6], Simonell et al. [7]).

Despite these advancements, the literature reveals several unresolved issues. First, while various models and methodologies exist for estimating external transport costs, a universally accepted framework remains absent, complicating cross-study comparisons and policy standardisation (Essen, H et al. [9], Spangenberg [10]). Additionally, real-world implementation of modal shifts faces economic and logistical barriers; for instance, road transport’s flexibility and cost advantages for shorter distances often hinder the effectiveness of multimodal strategies (Grzelakowski [4], Raza et al. [1]). Furthermore, the impact of regional policy differences on transport decisions across borders, especially within the EU, requires more empirical examination to optimise incentives and harmonise modal shift strategies across diverse transport networks.

Several debates persist within the literature, particularly concerning the cost-effectiveness of green supply chains that integrate modal shifts. For example, while some studies advocate for the economic viability of multimodal approaches, others argue that the high costs associated with rail and sea transport infrastructure improvements can limit feasibility, particularly in regions lacking robust port and rail facilities (Pinchasik et al. [3], Björk et al. [6]). Another point of contention involves the broader adoption of alternative fuels and advanced vehicle technology, which may reduce emissions within road transport, potentially lessening the push toward sea and rail options. Additionally, the precise social costs associated with transport emissions—spanning health, ecosystem degradation, and climate impacts—vary widely across studies, underscoring the need for more standardised approaches in quantifying these costs (Eslamipoor and Sepehriar, [8] Dominici et al. [11]).

One of the most detailed recent analyses is the “Handbook on the External Costs of Transport” prepared for the European Commission in 2019 [9]. This report evaluates the implementation of the ‘user pays’ and ‘polluter pays’ principles across EU Member States and other developed nations, providing a comprehensive overview of methodologies and inputs used to estimate primary external transport costs.

The research addresses the critical gaps in the current literature by providing a comprehensive framework for accurately estimating and internalising external transport costs, particularly in the context of European freight logistics. While previous studies, such as those by Raza et al. [1] and Björk et al. [6], have highlighted the challenges and benefits of modal shifts, they often lack a detailed analytical model that integrates environmental, economic, and social costs into a unified decision-making process. This article utilises the novel INCONE60 Cargo Flow Model, which is state-of-the-art in simulating cargo flows and quantifying external costs across transport modes, offering a more precise and actionable assessment compared to earlier approaches. By aligning our methodology with the European Commission’s 2019 “Handbook on the External Costs of Transport” [9], we provide a standardised and replicable framework that supports comparative analyses and enhances the verification of results across different regions and transport modes. Additionally, our research goes beyond previous studies by introducing a novel approach to evaluating policy implications for sustainable transport practices, bridging the gap between economic efficiency and environmental sustainability. This work advances the state-of-the-art by offering actionable insights for policymakers and logistics managers, providing practical solutions for reducing external costs and promoting sustainable modal shifts in global supply chains.

This study underscores the importance of incorporating external costs into logistics decision-making, supporting the development of policies that promote sustainable transport practices. The findings assist decision-makers in balancing economic efficiency with environmental stewardship, aligning with global sustainability goals and recent trends in transport policy. By analysing direct and external transport costs—including pollution, climate impact, and source-to-reservoir emissions—this research offers a comprehensive assessment that enhances the credibility of arguments in current transport policy debates.

2. Problem Defined

2.1. Evaluating Road Versus Maritime Transport

This study assesses road transport’s economic and environmental impacts compared to integrated maritime and land transport chains. It evaluates the direct and external costs of different transport modes, focusing on routes connecting small seaports in the Baltic and North Sea regions. By analysing these costs, the study informs policymaking and strategic planning in transport logistics, emphasising sustainability and cost-effectiveness.

2.1.1. Objectives

The primary objectives of this research are:

• Cost evaluation: Compare the direct costs of road transport with those of combined maritime and land transport chains on equivalent routes.
• External cost analysis: Analyse the external costs associated with each transport mode, including pollution, climate impact, and emissions from source to tank.
• Total cost assessment: Determine which transport mode offers a lower total cost when considering direct and external costs.
• Policy implications: Provide insights that support the development of more sustainable transport practices and efficient supply chain management.

2.1.2. Hypothesis

This study hypothesises that shifting from road to maritime transport can reduce total transport costs by increasing operational efficiency and promoting sustainability. The hypothesis posits that maritime transport incurs lower external costs due to greater energy efficiency and reduced emissions per unit of cargo, making it a more sustainable option than road transport.

3. Methods and Materials

3.1. The INCONE60 Model in Sustainable Transport Analysis

The INCONE60 Cargo Flow Model was selected for this study due to its versatility and effectiveness in analysing and optimising logistics and environmental impacts within European supply chains. Developed as part of the European INCONE60 project under the Interreg South Baltic Programme 2014–2020, the model aims to enhance transport logistics and infrastructure planning by optimising cargo flows between local and regional seaports [11]. Integrating multimodal data with detailed economic and environmental assessments, the INCONE60 model is an ideal tool for comparing road and sea transport modes in sustainability.

The INCONE60 model is a comprehensive transport simulation tool that accurately reflects common transport routes using data on shipping volumes, vessel capacities, and maritime spatial plans and integrates multimodal transport options. Its precision is enhanced by incorporating Geographic Information Systems (GIS), which ensure accurate distance calculations and route optimisation—crucial factors for reliable cost and environmental impact assessments. The model’s compliance with European Commission guidelines [9] further increases its utility in shaping sustainable transport policies.

One of the critical features of the INCONE60 model is its ability to simulate various logistics scenarios, allowing for an in-depth analysis of different strategies and their effects on external costs. By focusing on small regional seaports—critical components of local economies—the model provides a comprehensive mapping of the logistics network and highlights the importance of these ports in efficient and sustainable transport solutions.

3.2. Methodology

This study employed a structured methodology to analyse road and maritime transport’s economic and environmental implications. The methodology encompassed data collection, route mapping and optimisation, cost calculations, environmental impact assessment, and external cost estimation.

Data were gathered on 100 Baltic and North Sea routes where road and maritime transport are viable options. The selection criteria for these routes included geographical relevance—routes connecting small seaports to inland destinations within 150 km—cargo compatibility with standardised cargo types suitable for transport via both modes and operational feasibility based on the availability of data from transport operators and port authorities. The sources of data included transport operators, who provided information on transport costs, cargo volumes, vehicle and vessel specifications, and operational schedules; port authorities, who supplied data on port fees, handling charges, and infrastructure capabilities; and environmental agencies, which offered emission factors, ecological cost parameters, and guidelines for environmental impact assessments.

Geographic Information Systems (GIS) technology within the INCONE60 model was utilised to map and optimise routes for both transport modes. This process involved calculating precise distances for road and sea routes using GIS mapping tools, identifying the most efficient logistics pathways by considering factors such as travel time, fuel consumption, and infrastructure constraints, and ensuring that the selected routes for both transport modes were comparable in terms of origin, destination, and cargo characteristics.

Financial data from transport operators were integrated into the model to determine the direct costs associated with each transport mode. The cost components included fuel consumption, calculated based on distance, the fuel efficiency of vehicles and vessels, and current fuel prices; labour costs, which encompassed wages for drivers and crew members, accounting for working hours and labour regulations; maintenance expenses, covering routine maintenance, repairs, and depreciation of vehicles and vessels; port fees and tolls, accounting for charges related to port usage, docking, loading/unloading, and road tolls where applicable; and operational costs, including insurance, administrative expenses, and other overhead costs associated with transport operations. By incorporating detailed cost parameters, the model enabled a comprehensive analysis of the economic efficiency of each transport mode.

Environmental impacts were assessed using guidelines from the European Commission, incorporating emission factors and ecological cost parameters [9]. The assessment involved determining the quantities of pollutants emitted by each transport mode, including carbon dioxide (CO₂), nitrogen oxides (NO_X), sulfur oxides (SO_X), and particulate matter. Emission factors were specific to vehicle and vessel types, fuel types such as diesel and heavy fuel oil, and operating conditions like speed and load factors. These emission factors were sourced from authoritative databases provided by environmental agencies and standardised according to European regulations. The calculations reflected real-world conditions by considering variables such as fuel quality, engine efficiency, and emission control technologies to ensure accuracy.

External costs were estimated by translating environmental impacts into monetary values using established cost factors per tonne of pollutant emitted. This process included assessing health impact costs related to respiratory and cardiovascular diseases, hospital admissions, lost productivity, and premature mortality caused by air pollution [12]; estimating material degradation costs due to corrosion and soiling of buildings and infrastructure resulting from pollutants like SO_X and NO_X [13]; calculating agricultural and biodiversity costs resulting from losses in crop yields and ecosystem degradation caused by pollutants affecting plant health and biodiversity; and reflecting source-to-tank costs associated with the environmental impacts of fuel extraction, production, and distribution used in transport. The cost factors were derived from the European Commission’s Handbook on the External Costs of Transport [9], ensuring consistency and reliability in the estimations.

By applying the INCONE60 model, the study simulated two primary transport scenarios. The baseline scenario analysed current transport conditions predominantly utilising road transport. In contrast, the alternative scenario simulated integrated sea-land routes, emphasising the use of small regional seaports and combining maritime and road transport. For each scenario, the model calculated direct and external costs, allowing for a comprehensive comparison of the total cost of ownership for different transport modes on selected trans-European routes.

The collected data and calculated costs were analysed to test the study’s hypothesis that road transport incurs higher external costs than combined maritime and land transport chains. Statistical analyses included descriptive statistics to summarise data using means, medians, standard deviations, and ranges; normality testing by applying the Shapiro–Wilk test to assess the normality of cost distributions; variance analysis using Levene’s test to evaluate the homogeneity of variances between transport modes; and hypothesis testing by conducting t-tests (Welch’s t-test where variances were unequal) to compare mean costs and determine statistical significance. These analyses demonstrated how the hypotheses were tested, providing empirical support for the study’s conclusions.

4. Significance and Alignment with Global Sustainability Goals

Applying the INCONE60 model demonstrates the potential economic and environmental benefits of shifting freight from road to maritime routes. By providing empirical evidence supporting the hypothesis that combined maritime and land transport chains have lower external costs than road transport alone, the study aligns with global sustainability goals and trends in transport policy.

Recent studies emphasise the importance of green supply chain management and the role of strategic policies in promoting sustainable practices. For instance, strategies for a green centralised supply chain with deteriorating products highlight the need for enhancing supply chain relationships within the circular economy [14]. Additionally, promoting green supply chains under carbon tax, carbon cap, and carbon trading policies has been recognised as crucial for reducing carbon emissions in the transport sector [15].

By incorporating these recent findings into the analysis, the study strengthens its theoretical framework and provides greater context. The INCONE60 model’s ability to integrate external costs into logistics decision-making supports the development of policies that promote sustainable transport practices. This aligns with global sustainability goals such as the United Nations Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 13 (Climate Action).

Furthermore, the model’s comprehensive approach to assessing economic and environmental factors enhances its relevance to current transport policy debates. The study contributes to formulating strategies that balance economic efficiency with environmental stewardship by providing actionable insights for policymakers and stakeholders.

In summary, the INCONE60 Cargo Flow Model is a vital tool in sustainable transport analysis, offering a robust framework for comparing road and maritime transport’s direct and external costs. By utilising detailed data and adhering to standardised methodologies, the model provides reliable and comparable estimates that inform policy decisions and promote sustainable practices in global trade. Integrating recent research findings and aligning with global sustainability goals further enhances the study’s contribution to the field.

5. Results

Comparative Cost-Effectiveness Analysis of Road and Maritime Transport

An in-depth analysis of transport costs across 100 routes was conducted using data from the INCONE60 Cargo Flow Model to compare road and maritime transport. The study aimed to evaluate the direct costs of each transport mode and assess their cost-effectiveness, mainly focusing on routes in coastal areas up to 150 km inland where maritime transport is more competitive.

To ensure comparability, standard units were used for calculations. Maritime transport was represented by a vessel with a cargo capacity of 1500 deadweight tons (DWT), reflecting typical small to medium-sized cargo ships used in regional trade. Road transport was represented by a tractor unit with a semi-trailer capable of carrying 24 t. Approximately 62 such trucks would be required to match the cargo capacity of one vessel, highlighting the significant difference in carrying capacity between these modalities.

Data on transport costs were collected from transport operators. They included fuel consumption, labour, maintenance, port fees, tolls, and other operational costs. The selected routes were those where both road and maritime transport were viable options, ensuring a fair comparison. The INCONE60 model was utilised to calculate the direct costs for both transport modes on the 100 selected routes.

Statistical analyses were conducted to compare the direct costs between road and maritime transport. Descriptive statistics were calculated for each transport mode, including mean, median, standard deviation, and interquartile range and presented in

Table 1. Statistical summary of direct transport costs.

Statistic	Land Transport (€)	Sea Transport (€)
Mean Cost	170,318.07	13,785.36
Standard Deviation	72,082.78	3818.82
Range	56,446.00–333,955.93	8610.00–22,444.18
Median	170,827.23	13,486.64
Interquartile Range	115,496.27–219,037.32	10,561.86–16,611.73

. The Shapiro–Wilk test was applied to assess the normality of the cost distributions, and Levene’s test was used to evaluate the homogeneity of variances. Since the variances were unequal, Welch’s t-test was employed to compare the mean costs between the two transport modes.

The mean cost for road transport was €170,318.07, while for maritime transport, it was significantly lower at €13,785.36. Road transport costs exhibited more significant variability, as indicated by a standard deviation of €72,082.78, compared to €3818.82 for maritime transport. Factors contributing to this variability in road transport costs include infrastructure conditions, regulatory environments, fuel prices, and geographical constraints. In contrast, maritime transport demonstrated lower and more stable costs, attributed to standardised operations and economies of scale.

Statistical testing confirmed the significance of these cost differences. The Shapiro–Wilk test indicated that cost distributions for both transport modes were approximately normal. Levene’s test showed significant differences in variances (p < 0.05), justifying the use of Welch’s t-test. The Welch’s t-test results indicated a statistically significant difference in mean costs between road and maritime transport (t = 38.91, p < 0.0001), supporting the hypothesis that maritime transport is more cost-effective than road transport on the analysed routes.

These findings suggest that integrating maritime transport into regional logistics systems can lead to significant cost savings. The substantial difference in mean costs indicates that maritime transport can be a more economically efficient option, particularly over longer distances and in coastal areas where maritime routes are available.

The economic advantages of maritime transport are largely due to its ability to move large cargo volumes more efficiently, benefiting from economies of scale. Also, maritime transport typically incurs lower fuel costs per tonne-kilometre and lower labour costs per unit of cargo transported, as fewer crew members are required than the number of drivers needed for equivalent road transport.

These results have important implications for policymakers and logistics planners aiming to enhance economic efficiency and environmental sustainability in transport networks. By leveraging the cost-effectiveness of maritime transport, supply chains can be optimised, leading to reduced transportation costs and potentially lower prices for consumers.

The comparative analysis demonstrates that maritime transport offers substantial cost advantages over road transport on the analysed routes. The findings support the hypothesis that maritime transport is more cost-effective when considering direct and external costs. By integrating maritime transport into logistics planning, stakeholders can achieve economic efficiency while contributing to global sustainability goals. These results provide empirical support for policy interventions that promote modal shifts towards more sustainable transport modes, aligning with global efforts to promote sustainable transport solutions.

6. Comparative Analysis of External Costs in Land and Maritime Transport

A comprehensive statistical evaluation of environmental costs for road and maritime transport across 100 routes was conducted, revealing significant differences between these modes. Air pollution from transport generates substantial health impacts, material degradation, and losses in agriculture and biodiversity. Research by Dominici et al. (2014) demonstrated a direct link between particulate matter in the air and severe respiratory and cardiovascular diseases, leading to heightened mortality rates [16]. Epidemiological studies further support the connection between prolonged exposure to air pollution and chronic conditions such as asthma and cardiovascular disease [17].

Reports from the United Nations Economic Commission for Europe (UNECE) highlight that emissions of nitrogen oxides (NO_X) and sulfur dioxide (SO₂) cause environmental acidification, deteriorating buildings, and damaging structural materials [13]. For example, the annual maintenance cost to clean the limestone surface of the Colosseum in Rome is estimated at around €680,000 due to pollution-induced degradation. Similar impacts are evident in UNESCO World Heritage Sites like the Royal Palace of Caserta in Italy, where corrosion and soiling are significant. Air pollutants like ground-level ozone damage plants, reduce agricultural yields and impair plant health. High nitrogen levels can lead to eutrophication of waters, causing algal blooms and reduced oxygen levels, resulting in aquatic organisms’ death and biodiversity loss [18].

The INCONE60 Cargo Flow Model played a crucial role in this analysis by simulating and optimising transport logistics. It enabled precise mapping of transport routes, cost optimisation, and analysis of the environmental impact of different transport modalities. Its ability to integrate multimodal transport data and provide detailed economic and environmental assessments made it an ideal tool for this research [11].

A bottom-up method was employed to estimate the external costs of air pollution from road and maritime transport. The methodology involved evaluating the quantity of emissions alongside cost factors per tonne of pollutants. Emissions were calculated using average emission factors tailored to each vehicle and vessel type refined based on transport data from operators and environmental agencies.

The INCONE60 model calculated external costs through several key steps. First, it collected input data on emissions from different transport sources, including land vehicles and marine vessels. These figures encompassed greenhouse gas emissions such as carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄), as well as other air pollutants like NO_X, SO_X, and particulate matter (PM). Operational data such as transport routes, distances, fuel consumption, vehicle and vessel types, and trip frequency were also included.

Emissions were then estimated using emission factors specific to vehicle and vessel types and fuel types by combining fuel consumption with the corresponding emission factors for each pollutant. The emission factors were sourced from authoritative databases provided by environmental agencies and standardised according to European regulations [19]. This ensured that the calculations reflected real-world conditions by considering variables such as fuel quality, engine efficiency, and emission control technologies.

Next, the model calculated external costs, including health costs, material degradation costs, agricultural losses, and biodiversity loss costs. Health costs were calculated based on epidemiological data on the impact of air pollution on human health, considering the costs of treating respiratory and cardiovascular diseases and the costs associated with premature mortality [17,20]. Material costs resulting from corrosion of buildings and infrastructure were estimated based on the impact of acid rain and other contaminants on these structures, including maintenance and repair costs [12]. Agricultural costs were calculated based on the impact of air pollutants such as ozone on crop yields, considering losses in agricultural production and the associated economic costs [18]. Biodiversity loss costs stem from the impact of pollution on ecosystems, including the effects of eutrophication and acidification of waters.

The INCONE60 model also incorporated the Life Cycle Assessment (LCA) of transport, accounting for the emissions and costs related to the production, operation, and disposal of vehicles and transport infrastructure [21]. An LCA provided a comprehensive understanding of environmental costs, covering the entire spectrum from raw material extraction to final disposal.

Finally, external costs were aggregated and presented in reports that provided detailed cost breakdowns for different categories and transport modalities. These reports empowered decision-makers and logistics planners to make informed choices that foster sustainability and reduce the environmental impact of transportation. With its comprehensive logistics analysis and optimisation approach, the INCONE60 model supported more sustainable and efficient practices in the transport sector.

An example of a report generated from the model is illustrated in Figure 1, showcasing a comparison of the costs associated with road and sea transport between the ports of Klaipėda and Oostende. The analysis revealed significant differences in direct and environmental costs, clearly indicating the advantages of maritime transport over road transport.

Road transport on the Klaipėda–Oostende route covered a distance of 2029.90 km, with a total transport cost of €153,460.52, using 63 curtainsider trucks. In contrast, sea transport on the same route, with a length of 1417.74 km, carried out with a single vessel named “Jennifer”, incurred costs of only €63,190.00. Road transport also generated significantly higher environmental costs, amounting to €128,797.22, while maritime transport had considerably lower costs of €25,993.99.

Statistical tests confirmed significant differences in environmental costs between road and maritime transport. The t-test results revealed significant differences in pollution costs and climate impact, with road transport being notably more expensive than maritime transport. The p-values for pollutants and climate impact were 0.018 and 0.015, respectively, rejecting the null hypothesis of no difference between the costs of these modalities.

The data in

Table 2. Results of the statistical analysis of environmental costs.

Category	Title 2	Title 3
The cost of pollution	19,703.84	4756.48
The cost of climate impact	9508.01	2419.03
Cost from source to tank	14,956.03	3888.76
Standard Deviation (Land Transport)	4783.99	-

demonstrate pronounced disparities in environmental costs between road and maritime transport. The cost of pollution in road transport is approximately four times higher than in maritime transport, mainly due to higher emission rates and less stringent regulations. Climate impact costs for road transport are also much higher, nearly four times greater than those for maritime transport, due to the higher carbon footprint and inefficiencies of road vehicle technology. Source-to-tank costs in road transport are significantly higher, suggesting a less efficient fuel logistics chain.

These results highlight the higher environmental costs of road transport, especially concerning pollution and climate impacts, suggesting the environmental benefits of choosing maritime transport. Higher road transport costs result from higher fuel consumption and lower energy efficiency, exacerbated by various technologies and operating conditions. Maritime freight exhibits less cost volatility, reflecting standardised operations and compliance with international standards.

The findings underscore the need to integrate environmental considerations into logistics planning. The data point to the necessity for stricter regulation of road transport and technological advances in vehicle efficiency and cleaner fuels. The relatively sustainable nature of maritime transport suggests its strategic role in multimodal transport solutions.

Recent studies emphasise the importance of promoting green supply chains under carbon tax, carbon cap, and carbon trading policies [15] and enhancing supply chain relationships in the circular economy [14]. Aligning transport strategies with these trends can contribute to global sustainability goals and reduce environmental impacts.

In conclusion, the comparative analysis of external costs underscores the significant environmental benefits of maritime transport over road transport. Policymakers and stakeholders should consider these findings when developing strategies and policies to promote sustainable transport practices, supporting economic efficiency and environmental stewardship. By choosing maritime transport, logistics planners can reduce environmental impacts while maintaining efficient supply chains, aligning with the Sustainable Development Goals (SDGs) and recent trends in transport policy [22].

7. Implications for Sustainable Transport Policy

The findings of this study have significant implications for sustainable transport policy, highlighting the critical role of the INCONE60 Cargo Flow Model in shaping strategies that promote environmental sustainability and economic efficiency. By providing a comprehensive framework for analysing and optimising logistics and environmental impacts in European supply chains, the INCONE60 model is a valuable tool for policymakers and stakeholders. Its ability to integrate multimodal data and deliver detailed economic and environmental assessments enables a thorough understanding of the full impacts of different transport modes.

The empirical evidence from the model demonstrates that maritime transport incurs lower direct and external costs than road transport. This supports the hypothesis that shifting freight from road to maritime routes can significantly reduce transport costs and environmental impacts. By quantifying these differences, the model aids in crafting policies that encourage modal shifts from road to sea transport, leveraging maritime logistics’ environmental and economic benefits. The detailed simulation capabilities of the INCONE60 model allow for the evaluation of various transport scenarios, offering insights into the most efficient and sustainable logistics strategies.

Policymakers can use these insights to support decisions that reduce external costs, such as air pollution and greenhouse gas emissions while maintaining economic efficiency. The evidence-based approach ensures that policies are rooted in empirical data, improving their effectiveness and increasing public acceptance. Given the lower environmental costs of maritime transport highlighted by the model, policies can be designed to incentivise the use of sea transport, particularly for long-distance and coastal routes. Measures such as subsidies, tax incentives, and investments in port infrastructure can be introduced to support this modal shift, aligning transport strategies with sustainability goals.

The model also underscores the need for stricter environmental regulations for road transport. By quantifying the higher external costs associated with road transport, the findings support implementing stringent emission standards and promoting These regulatory measures, which can significantly reduce the environmental footprint of land transport. Furthermore, the findings advocate for strategic maritime and road infrastructure investments. Upgrading ports and improving intermodal connections can enhance the efficiency and appeal of maritime transport. Simultaneously, improving road infrastructure can mitigate congestion, enhance fuel efficiency, and reduce environmental impacts, contributing to a more sustainable transport network.

The comprehensive approach of the INCONE60 model to assessing external costs highlights the need for ongoing research and development in sustainable transport technologies and logistics solutions. Stakeholders can promote sustainability in the transport sector by continually refining methodologies for calculating external costs and exploring innovative transport strategies. The model’s ability to provide precise data on direct and external costs enables stakeholders to make informed decisions that balance economic efficiency with environmental stewardship.

In conclusion, the INCONE60 Cargo Flow Model offers invaluable insights that can transform transport policy and logistics planning. By emphasising maritime transport’s economic and environmental benefits and offering a robust framework for evaluating external costs, the model promotes the creation of sustainable transport systems that align with global environmental objectives and economic efficiency. Incorporating these findings into policy and practice is crucial for advancing sustainable development in the transport sector.

The study’s findings align with global efforts to reduce greenhouse gas emissions and promote sustainable development. They support the United Nations Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 13 (Climate Action). By promoting sustainable transport practices, the research contributes to commitments under the Paris Agreement to limit the rise in global temperature. It also aligns with the European Green Deal and the European Commission’s Sustainable and Smart Mobility Strategy, which aim to reduce emissions from the transport sector and promote cleaner modes of transportation.

This research provides empirical evidence supporting the significant economic and environmental benefits of shifting freight from road to maritime transport. By utilising the INCONE60 Cargo Flow Model, the study quantified and compared both modes’ direct and external costs, confirming the hypotheses that maritime transport is more cost-effective and environmentally sustainable. The findings underscore the importance of integrating external costs into decision-making processes and highlight the critical role of strategic modal shifts in achieving global sustainability goals.

Policymakers and stakeholders are encouraged to consider these results when developing strategies and policies to promote sustainable transport practices. By leveraging the advantages of maritime transport and implementing supportive policies, it is possible to reduce external costs, enhance economic efficiency, and contribute to environmental stewardship. Adopting such strategies is essential for advancing sustainable development in the transport sector and aligning with international commitments to combat climate change.

8. Conclusions

This study has highlighted road transport’s significant economic and environmental impacts compared to integrated land and sea transport chains. Utilising the INCONE60 Cargo Flow Model, we conducted a comprehensive analysis that revealed the considerable external costs incurred by different transport modes, particularly emphasising the higher costs associated with road transport. The empirical findings support the hypothesis that road transport generates higher external costs due to greater emissions and health-related impacts. In contrast, maritime transport offers a more sustainable alternative owing to its lower emissions per unit of cargo transported and greater fuel efficiency.

The INCONE60 model proved invaluable in this research by providing precise and detailed assessments of direct and external costs. By integrating data from different transport modes and offering comprehensive cost evaluations, the model facilitated a thorough comparison that confirmed maritime transport reduces external costs and supports broader sustainability goals. The statistical analyses, including t-tests and variance assessments, demonstrated significant differences in costs between road and maritime transport, thereby validating the study’s hypotheses and providing robust empirical support for our conclusions.

The implications of this study are far-reaching for sustainable transport policy. Policymakers are encouraged to promote maritime transport by implementing subsidies, tax incentives, and investments in port infrastructure to enhance its capacity and efficiency. Such measures can significantly reduce the environmental footprint of freight transport by encouraging a modal shift from road to sea. Strengthening environmental regulations for road transport is also crucial. Implementing stricter emission standards and promoting cleaner technologies, such as electric and hybrid vehicles, can mitigate the higher external costs associated with road transport. These regulatory measures are supported by the study’s findings, which quantify the environmental benefits of reducing emissions from road transport.

Investing in infrastructure to enhance intermodal connectivity is essential to facilitate seamless transitions between transport modes. Improvements in ports, rail connections, and road networks are crucial for optimising the logistics chain and improving efficiency. The study’s results underscore the importance of such investments by demonstrating how integrated transport networks can lead to significant cost savings and environmental benefits.

Furthermore, the utilisation of advanced modelling tools like the INCONE60 Cargo Flow Model in transport planning and policymaking is strongly recommended. These tools provide valuable insights into cost structures and environmental impacts, guiding more informed and sustainable decisions. By incorporating external costs into transport pricing and policy development, stakeholders can incentivise the selection of more sustainable transport modes and reduce the overall environmental impact of freight transport.

Fostering collaboration between academia, industry, and government agencies is vital for continually refining external cost models and developing innovative solutions for sustainable transport. Such collaborative efforts can drive technological advancements and policy innovations that support greener logistics practices. The study highlights the need for ongoing research and development in this area, suggesting that expanding the scope of analysis to include other transport modes, such as rail and air, would ensure a comprehensive understanding of external costs across all transport sectors. This holistic approach can further inform policy decisions and promote integrated, sustainable transport solutions.

In conclusion, the study underscores the vital role of the INCONE60 Cargo Flow Model in assessing and comparing the external costs associated with different transport modes. The findings confirm that maritime transport offers substantial economic and environmental advantages over road transport, particularly on routes where both modes are viable options. By providing empirical evidence that supports maritime transport’s economic efficiency and environmental sustainability, the research contributes to formulating strategies that promote more sustainable transport practices.

The study’s conclusions align with global efforts to reduce greenhouse gas emissions and promote sustainable development. They support the United Nations Sustainable Development Goals, particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 13 (Climate Action). By promoting sustainable transport practices, the research contributes to commitments under the Paris Agreement to limit the rise in global temperature. It also aligns with the European Green Deal and the European Commission’s Sustainable and Smart Mobility Strategy, which aim to reduce emissions from the transport sector and promote cleaner modes of transportation.

Incorporating these findings into policy and practice is crucial for advancing sustainable development in the transport sector. Policymakers and stakeholders are encouraged to leverage the advantages of maritime transport and implement supportive policies that facilitate modal shifts, reduce external costs, and enhance economic efficiency. Adopting such strategies is essential for achieving environmental and economic benefits, contributing to a more sustainable and efficient global logistics system.