Special Issue "Sustainable Transportation Systems Towards a Low Carbon Transition: Energy, Environmental and Behavioral Aspects"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (15 February 2020).

Special Issue Editors

Prof. Gianluca Scaccianoce
E-Mail Website
Guest Editor
Department of Engineering, University of Palermo, viale delle scienze bld 9, 90128 - Palermo, Italy
Interests: energy systems and technologies in the transportation sector; sustainable mobility; transportation environmental impacts; Acoustic and atmospheric impact of transportation sector; Renewable energy systems and technologies; Energy Performance of Buildings; Urban energy modelling and sustainability analysis
Prof. Maria La Gennusa
E-Mail Website
Guest Editor
Department of Engineering, University of Palermo, Palermo, 90128, Italy
Interests: ustainable development; Solar radiation; Energy efficiency; Thermal comfort; Urban transportation; Energy conservation; Energy utilization

Special Issue Information

Dear colleagues,

The transition towards a low-carbon society directly involves the transport sector, which is currently responsible for nearly 30% of the total final energy consumption, mostly utilizing fossil fuels and/or their derivatives. Hence, it is of paramount importance to reduce the dependence of the transport sector on such energy sources.

Clearly, this can be achieved by acting on the current means of transport technology (both public and private) and on the transport infrastructures, which must become safer and more resilient, and whose management can be conducted with a vision more suited to sustainability (roundabouts, traffic light time intervals, and so on).

On the other hand, new evidence concerning the modal change from private to the public means of transportation must be considered, since it can provide a strong contribution to the reduction of energy consumption and relative pollutant emissions.

Additionally, the path leading to the creation of smart cities tends to establish a strong link between urban transportation and buildings. The latter are, in fact, increasingly seen as nodes of electricity generation that can partially feed some urban electrical systems (subway, PV-shelters, charging columns, and so on).

Furthermore, users’ behaviour should be traced back to more sustainable transport systems, especially in urban areas.

Naturally, the pursuit of more efficient transportation systems has a direct influence on their environmental performances, making them less impactful in terms of pollutant emissions and levels of noise release and, therefore, more sustainable. For this reason, the applicability of the methods of analysis of the environmental performance of transportation systems (including their LCA and ecological footprint) needs to be deeply investigated.

In conclusion, all the above-cited issues should constitute the foundation for sustainable transport modelling.

High-quality papers addressing the above-mentioned issues (though not just limited to these) are solicited, with a particular interest in theoretical and experimental analyses with the aim to provide new methods, new indicators, or new data that is useful for the evaluation and the achievement of sustainable transportation systems.

Prof. Dr. Gianluca Scaccianoce
Prof. Dr. Maria La Gennusa
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Transportation systems
  • Energy efficiency
  • Renewable energy systems
  • Environmental impact
  • Transport and infrastructures
  • ICT, IoT, and big data
  • Logistics
  • Smart cities and urban transportation
  • Mobilty policies
  • Maritime transport
  • Behavioural aspects

Published Papers (6 papers)

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Research

Open AccessArticle
Long-Term Forecast of Energy and Fuels Demand Towards a Sustainable Road Transport Sector in Ecuador (2016–2035): A LEAP Model Application
Sustainability 2020, 12(2), 472; https://doi.org/10.3390/su12020472 - 08 Jan 2020
Abstract
The total energy demand in the transport sector represented 48.80% of the total consumption in Ecuador throughout 2016, where 89.87% corresponded to the road transport sector. Therefore, it is crucial to analyze the future behavior of this sector and assess the economic and [...] Read more.
The total energy demand in the transport sector represented 48.80% of the total consumption in Ecuador throughout 2016, where 89.87% corresponded to the road transport sector. Therefore, it is crucial to analyze the future behavior of this sector and assess the economic and environmental measures towards sustainable development. Consequently, this study analyzed: (1) the total energy demand for each vehicle class and fuel type; (2) the GHG (greenhouse gas) emissions and air pollutants NOx and PM10; and (3) the cost attributed to the fuel demand, between 2016 and 2035. For this, four alternative demand scenarios were designed: BAU: Business As Usual; EOM: Energy Optimization and Mitigation; AF: Alternative Fuels; and SM: Sustainable Mobility using Long-range Energy Alternatives Planning system. After analysis, the EOM, AF, and SM scenarios have advantages relative to BAU, where SM particularly stands out. The results show that SM compared to BAU, contributes with a 12.14% (141,226 kBOE) decrease of the total energy demand, and the economic savings for this fuel demand is of 14.22% (26,720 MUSD). Moreover, global NOx and PM10 emissions decreased by 14.91% and 13.78%, respectively. Additionally, accumulated GHG emissions decreased by 13.49% due to the improvement of the fuel quality for the vehicles that mainly consume liquefied petroleum gas, natural gas, and electricity. Full article
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Open AccessArticle
Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation
Sustainability 2019, 11(23), 6705; https://doi.org/10.3390/su11236705 - 27 Nov 2019
Abstract
Research assessing on-road emission flow patterns from motor vehicles is essential in monitoring urban air quality, since it helps to mitigate atmospheric pollution levels. To reveal the influence of vehicle induced turbulence (VIT) caused by both front- and rear-vehicles on traffic exhaust and [...] Read more.
Research assessing on-road emission flow patterns from motor vehicles is essential in monitoring urban air quality, since it helps to mitigate atmospheric pollution levels. To reveal the influence of vehicle induced turbulence (VIT) caused by both front- and rear-vehicles on traffic exhaust and verify the applicability of the simplified line source emission model, a Computational Fluid Dynamics (CFD) numerical simulation was used to investigate the micro-scale vehicle pollutant flow patterns. The simulation results were examined through sensitivity analysis and compared with the field measured carbon monoxide (CO) concentration. Conclusions indicate that the vehicle induced turbulence caused by the airflow blocking effect of both front- and rear-vehicles impedes the diffusion of front-vehicle traffic exhaust, compared with that of the rear vehicle. The front-vehicle isosurface with the CO mass fraction of 0.0012 extended to 6.0 m behind the vehicle, while that of the rear-vehicle extends as far as 12.7 m. But for the entire motorcade, VIT is beneficial to the diffusion of pollutants in car-following situations. Meanwhile, within the range of 9 m behind the rear of the lagging vehicle lies a vehicle induced turbulence zone. Furthermore, the influence of vehicle induced turbulence on traffic exhaust flow pattern is obvious within a range of 1 m on both sides of the vehicle body, where the concentration gradient of on-road emission is larger and contains severe mechanical turbulence. As a result, in the large concentration gradient area of the pollutant flow field, which accounts for 99.85% of the total concentration gradient, using the line source models to represent the on-road emission might introduce considerable errors due to neglecting the influence of vehicle induced turbulence. Findings of this study may shed lights on predicting emission concentrations in multiple locations by selecting appropriate on-road emission source models. Full article
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Open AccessArticle
Towards Carbon-Neutral Mobility in Finland: Mobility and Life Satisfaction in Day-to-Day Life
Sustainability 2019, 11(19), 5374; https://doi.org/10.3390/su11195374 - 28 Sep 2019
Cited by 1
Abstract
Finland, a prosperous Nordic country with a population of 5.5 million and significant distances between towns, though quite short distances traveled by car, is aiming to be a carbon-neutral society by 2035. Due to the level of urgency, a technological pathway with decarbonization [...] Read more.
Finland, a prosperous Nordic country with a population of 5.5 million and significant distances between towns, though quite short distances traveled by car, is aiming to be a carbon-neutral society by 2035. Due to the level of urgency, a technological pathway with decarbonization of fuels and innovation only, is unlikely to be sufficient. Instead, a more systemic change based on a transformative pathway with demand-side management, i.e., measures based on behavioral change, is vital. In this research we were interested in learning how life satisfaction relates to the behavioral intentions of Finnish citizens, regarding a sustainable modal shift. We focused on walking, cycling, public transport and reduction in car use, e.g., a transition from fossil fuels to active mobility, from ownership to usership. Data were collected via a questionnaire in April 2017. The respondents (n = 2052) provided 2335 comments as to why they considered a specific sustainable modality as being important to them. We applied both qualitative and quantitative methods in order to establish how the mobility behavior of citizens manifests nationwide and the types of arguments that citizens put forward concerning their mobility intentions. The results indicate that there is a strong relationship between the respondents’ reduced use of private cars and their life satisfaction. There is a concern about sustainability and a willingness to change current mobility practices, as well as signs of altruism, while hedonic concerns such as health and personal finances dominate the responses. Furthermore, concerns about social injustice, such as a lack of public transport, are emerging themes, i.e., when enacting mobility transitions it is vital to focus on how to enable a meaningful life for all demographic groups using suitable mobility services. Full article
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Open AccessArticle
Roles of Psychological Resistance to Change Factors and Heterogeneity in Car Stickiness and Transit Loyalty in Mode Shift Behavior: A Hybrid Choice Approach
Sustainability 2019, 11(17), 4813; https://doi.org/10.3390/su11174813 - 03 Sep 2019
Abstract
To support the scientific policy making and planning for promoting the share rate of sustainable public transit in urban areas of large metropolises, this study analyzes the influences of psychological resistance to change factors on commuters’ mode shift behavior while some external changes [...] Read more.
To support the scientific policy making and planning for promoting the share rate of sustainable public transit in urban areas of large metropolises, this study analyzes the influences of psychological resistance to change factors on commuters’ mode shift behavior while some external changes happen in the transport supplies. The heterogeneities in the car users’ stickiness to car and the metro users’ loyalty to metro are examined to support individual-specific travel behavior prediction. Web-scripted efficient experimental stated preference surveys including four commuting modes and three key factors are generated, and face-to-face interviews are conducted to collect reliable behavioral data. A hybrid choice approach, simultaneously considering the latent variables and quantitative level-of-service variables of different options, is employed for analysis. The results indicate that psychological resistance to change factors (routine seeking, cognitive rigidity, and emotion reaction) have significant and substantial influences on car users’ inclination to previously used commuting mode (i.e., car) in mode shift behavior. Car users with stronger routine seeking, stronger cognitive rigidity, and less emotion reaction show more predilection to car. Car users’ income level, gender, marital status, commuting distance, commuting time, license type, and flexible work time are found to partially explain the heterogeneity in car stickiness. In-vehicle crowding of public transit is a much more crucial factor for attracting car users to shift to public transit as compared to cost and travel time. Metro users with stronger routine seeking and less emotion reaction present a stronger inclination to metro in mode shift behavior. The influences of psychological resistance to change factors on metro users’ mode shift behavior are comparatively smaller than the influences of these factors on car users’ behavior. Metro users’ age, education level, commuting distance, commuting time, occupation, and flexible work time are identified to be associated with predilections for metro. Full article
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Open AccessArticle
Research on Group Choice Behavior in Green Travel Based on Planned Behavior Theory and Complex Network
Sustainability 2019, 11(14), 3765; https://doi.org/10.3390/su11143765 - 10 Jul 2019
Abstract
Motor vehicle exhaust emissions have made air pollution increasingly serious in China, and advocating for the concept of green travel can help alleviate the air pollution caused by motor vehicle exhaust. Thus, the research on the green travel choice behavior of limited rational [...] Read more.
Motor vehicle exhaust emissions have made air pollution increasingly serious in China, and advocating for the concept of green travel can help alleviate the air pollution caused by motor vehicle exhaust. Thus, the research on the green travel choice behavior of limited rational individuals in the complex social network and the evolution of group behavior is the focus of this paper. Based on the theory of planned behavior, this paper established the individual cognition-behavior model. Meanwhile, an interaction model of individuals in the network is constructed based on the DeGroot model and scale-free network. The simulation results of the model show that: (1) it is difficult to control the behavior of green travel: even if the knowledge level of green travel is high, the proportion of green travel individuals in the group is still very low; (2) the individual intention for green travel is dependent on behavioral attitude, which can effectively improve the proportion of green travel individuals; (3) if the individual intention is too dependent on the subjective norm and the perception of behavioral result, the proportion of green travel individuals would become lower; and (4) when the network is connected, the proportion of individuals who choose green travel will reach the peak through social interaction and learning. This study has a certain practical significance for the environmental protection work of relevant departments, which can guide the behavior of individuals through the design of government institutions, and enable the concept of green travel to form an ideology by means of education and knowledge dissemination, so as to generate some kind of consensual behavioral consciousness. Meanwhile, this study provides a new research perspective for behavioral research and extends the research scope of group behavior. Full article
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Open AccessArticle
Carbon Emissions and Expressway Traffic Flow Patterns in China
Sustainability 2019, 11(10), 2824; https://doi.org/10.3390/su11102824 - 17 May 2019
Cited by 2
Abstract
Traffic flow patterns severely impact vehicle carbon emissions. A field test was conducted in this study to obtain fuel consumption and traffic volume data under various traffic flow patterns and to explore the relationship between traffic flow patterns and vehicle carbon emissions. Carbon [...] Read more.
Traffic flow patterns severely impact vehicle carbon emissions. A field test was conducted in this study to obtain fuel consumption and traffic volume data under various traffic flow patterns and to explore the relationship between traffic flow patterns and vehicle carbon emissions. Carbon emission data were obtained via the indirect carbon emission accounting method proposed by the Intergovernmental Panel on Climate Change. Carbon emission prediction models for diesel trucks and gasoline passenger cars were established respectively with volume to capacity ratio as an explanatory variable. The results show that carbon emissions are highest under the congested flow conditions, followed by unstable flow, free flow, and steady flow. The relationship between the volume to capacity ratio and carbon emissions is a cubic curve function. The carbon emissions of trucks and passenger cars with a volume to capacity ratio of 0.4 to 0.5 are relatively small. The proposed carbon emissions models effectively quantify the carbon emissions of vehicles under different traffic flow patterns. The results of this study may provide data to support and a workable reference for expressway operation management and future low-carbon expressway expansion construction projects. Full article
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