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Special Issue "Sustainable Transportation for Sustainable Cities"

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

Deadline for manuscript submissions: 15 May 2019

Special Issue Editor

Guest Editor
Prof. Dr. Daniel Albalate

Departament d’Econometria, Estadística i Economia Aplicada; Facultat d’Economia i Empresa, Universitat de Barcelona, 08034 Barcelona, Spain
Website | E-Mail
Interests: transport policy; infrastructure; policy evaluation

Special Issue Information

Dear Colleagues,

Cities worldwide face increasingly unsustainable mobility patterns as they become more dependent on the car. Urban transport becomes an essential challenge for local policy makers needing innovative policies sustained and supported by scientific research evidence that might help in the fight against traffic congestion, environmental degradation, climate change and health and safety perils. This Special Issue includes academic works providing evidence on new paradigms of sustainable transportation policy for cities. Sustainable transportation covers environmental, social and economic dimensions and require a multi-disciplinary approach to examine, explore and critically engage with issues and advances leading to more sustainable cities. A variety of topics and policy measures are welcome: reduction of fossil fuels’ dependence, promotion of renewal and regenerated energy technology—as electric vehicles and their challenges and opportunities—regulation and planning, provision of new transportation modes, collaborative and shared economy initiatives, etc. The issue aims to encourage an informed and rigorous debate on sustainable mobility and transport policies in cities.

Prof. Dr. Daniel Albalate
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 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

  • Sustainability
  • Transportation
  • Mobility
  • Cities
  • Transport Policy

Published Papers (5 papers)

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Research

Open AccessArticle Evaluating the Efficacy of Zero-Emission Vehicle Deployment Strategies: The Maryland Case
Sustainability 2019, 11(6), 1750; https://doi.org/10.3390/su11061750 (registering DOI)
Received: 28 February 2019 / Revised: 12 March 2019 / Accepted: 18 March 2019 / Published: 22 March 2019
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Abstract
This study aimed to develop a model to estimate the impacts of zero-emission vehicle (ZEV) adoption on CO2 emissions and to evaluate efficacy of ZEV deployment strategies in achieving greenhouse gas (GHG) emission reduction goals. We proposed a modeling scheme to represent [...] Read more.
This study aimed to develop a model to estimate the impacts of zero-emission vehicle (ZEV) adoption on CO2 emissions and to evaluate efficacy of ZEV deployment strategies in achieving greenhouse gas (GHG) emission reduction goals. We proposed a modeling scheme to represent ZEVs in four-step trip-based travel demand models. We then tested six ZEV scenarios that were a cross-combination of three ZEV ownership levels and two ZEV operating cost levels. The proposed modeling scheme and scenarios were implemented on the Maryland Statewide Transportation Model (MSTM) to analyze the impacts of different ZEV ownership and cost combinations on travel patterns and on CO2 emissions. The main findings were the following: (1) A high-ZEV ownership scenario (43.14% of households with ZEVs) could achieve about a 16% reduction in statewide carbon dioxide equivalent (CO2Eq) emissions from 2015 base year levels; and (2) CO2Eq emissions at a future year baseline (2030) (the Constrained Long-Range Plan) level dropped by approximately 11% in low-ZEV ownership scenarios, 17% in medium-ZEV ownership scenarios, and 32% in high-ZEV ownership scenarios. The high-ZEV ownership results also indicated a more balanced distribution of emissions per unit area or per vehicle mile traveled among different counties. Full article
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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Open AccessArticle Operating Charging Infrastructure in China to Achieve Sustainable Transportation: The Choice between Company-Owned and Franchised Structures
Sustainability 2019, 11(6), 1549; https://doi.org/10.3390/su11061549
Received: 15 January 2019 / Revised: 1 March 2019 / Accepted: 6 March 2019 / Published: 14 March 2019
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Abstract
The rapid development of electric vehicles (EVs) is conducive to clean transportation, which is an important aspect of sustainable infrastructure. However, the introduction of EVs is constrained by the lagging development of EV chargers. To optimally promote the development of charging stations, we [...] Read more.
The rapid development of electric vehicles (EVs) is conducive to clean transportation, which is an important aspect of sustainable infrastructure. However, the introduction of EVs is constrained by the lagging development of EV chargers. To optimally promote the development of charging stations, we analyzed the differences in the optimal quality and quantity of EV chargers between company-owned and franchised enterprises by constructing a theoretical model, and the changes in the quality and quantity of EV chargers in different market environments are discussed. We found that the total number of franchised charging stations was larger in general, but that the quality of the franchised charging stations was worse compared with the company-owned stations. The supervision cost, operation cost, and the investment return affect the quality and quantity of EV chargers. Although franchised structures are more conducive in the initial stage to increasing the number of charging stations to meet the needs of EVs, company-owned structures perform better and will be needed to improve the quality of the EV chargers as the market becomes more saturated, necessitating a higher quality of EV chargers. Full article
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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Open AccessArticle Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data
Sustainability 2019, 11(3), 643; https://doi.org/10.3390/su11030643
Received: 17 December 2018 / Revised: 22 January 2019 / Accepted: 23 January 2019 / Published: 26 January 2019
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Abstract
Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. [...] Read more.
Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. This paper presents the approach to locate charging stations utilizing the reconstructed EVs trajectory derived from the Cellular Signaling Data (CSD). Most previous work focused on the commute trips estimated from the number of jobs and households between traffic analysis zones (TAZs). This paper investigated the large-scale CSD and illustrated the method to generate the 24-hour travel demand for each EV. The complete trip in a day for EV was reconstructed through merging the time sequenced trajectory derived from simulation. This paper proposed a two-step model that grouped the charging demand location into clusters and then identified the charging station site through optimization. The proposed approach was applied to investigate the charging behavior of medium-range EVs with Cellular Signaling Data collected from the China Unicom in Tianjin. The results indicate that over 50% of the charging stations are located within the central urban area. The developed approach could contribute to the planning of future charging stations. Full article
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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Open AccessArticle Effects of Perceived Traffic Risks, Noise, and Exhaust Smells on Bicyclist Behaviour: An Economic Evaluation
Sustainability 2019, 11(2), 408; https://doi.org/10.3390/su11020408
Received: 13 December 2018 / Revised: 5 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
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Abstract
Active mode (walking, bicycling, and their variants) users are exposed to various negative externalities from motor vehicle traffic, including injury risks, noise, and air pollutants. This directly harms the users of these modes and discourages their use, creating a self-reinforcing cycle of less [...] Read more.
Active mode (walking, bicycling, and their variants) users are exposed to various negative externalities from motor vehicle traffic, including injury risks, noise, and air pollutants. This directly harms the users of these modes and discourages their use, creating a self-reinforcing cycle of less active travel, more motorized travel, and more harmful effects. These impacts are widely recognized but seldom quantified. This study evaluates these impacts and their consequences by measuring the additional distances that bicyclists travel in order to avoid roads with heavy motor vehicle traffic, based on a sample of German-Austrian bicycle organization members (n = 491), and monetizes the incremental costs. The results indicate that survey respondents cycle an average 6.4% longer distances to avoid traffic impacts, including injury risks, air, and noise pollution. Using standard monetization methods, these detours are estimated to impose private costs of at least €0.24/cycle-km, plus increased external costs when travellers shift from non-motorized to motorized modes. Conventional transport planning tends to overlook these impacts, resulting in overinvestment in roadway expansions and underinvestments in other types of transport improvements, including sidewalks, crosswalks, bikelanes, paths, traffic calming, and speed reductions. These insights should have importance for transport planning and economics. Full article
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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Open AccessArticle Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway
Sustainability 2018, 10(12), 4725; https://doi.org/10.3390/su10124725
Received: 6 December 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
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Abstract
Urban rail transit has become an indispensable option for Beijing residents. Subway inelastic users (SIUs) are the main component among all users. Understanding the proportion of SIUs and their characteristics is important in developing service promotions and helpful for subway agencies in making [...] Read more.
Urban rail transit has become an indispensable option for Beijing residents. Subway inelastic users (SIUs) are the main component among all users. Understanding the proportion of SIUs and their characteristics is important in developing service promotions and helpful for subway agencies in making marketing policies. This paper proposes a novel and simple identification process for identifying regular subway inelastic trips (SITs) in order to distinguish SITs and non-SITs and extract their characteristics. Weekly station sequence (WSS) is selected as the data-based format, principles of SIUs are discussed and chosen, and the framework of SIT identification is applied to a large weekly sample from the Beijing Subway. A revealed preference (RP) survey and results analysis are undertaken to estimate the performance of the proposed methods. The RP survey validation shows that accuracy reaches as high as 94%, and the distribution analysis of SITs and their origin-destinations (ODs) indicate that the SIT characteristics extracted are consistent with the situation in Beijing. The proportion of SIUs is stable on workdays and is more than 80% during rush hour. The efforts described in this paper can provide subway managers with a useful and convenient method to understand the characteristics of subway passengers and the performance of a subway system. Full article
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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