Abstract

A quarter of energy-related greenhouse gas emissions (GHG) originate from the transportation sector. Continuously increasing demand for transportation services worldwide is one of the main urban challenges addressed by Sustainable Development Goal 11, target 2. One way to address this issue is to develop an integrated transportation system that can ensure confidence and comfort for the passengers. This will contribute not only to the customers’ experience but also to operators and authorities through sustainable, cost-effective, and profitable services. Conversely, the lack of such a system or a poorly managed system prevents the economy and society from realizing its potential. In the transition towards sustainability, the planning process of complex systems such as transportation often requires supportive tools and methods, such as futures methodologies that assist decision-making by providing information about possible futures. In today’s rapidly changing environment, forecasting tools do not always provide the expected outcomes since it is difficult to predict all the unexpected events. Therefore, there is a demand for alternative methods that not only grasp the constant changes but also create additional value (for example, meeting the needs of multisectoral collaboration and creation of common vision). The present article investigates the usefulness of three such methodologies, namely backcasting, foresighting, and SymbioCity, for the planning process of the bus park and railway station in Kisumu, Kenya, and Centralen in Gothenburg, Sweden. The paper’s contribution is a description of the Kenyan transportation system (which has not been studied in detail before), planning process, and pertinent issues related to the stations both in Kisumu and Gothenburg, located in the sharply contrasting contexts of global South and global North, respectively. On the basis of field research, interviews, and feasibility study of futures methodologies, the paper concludes that backcasting is the most suitable of the methodologies for both places, since it can be applied at a small scale, and provides creative solutions and has a high level of integration of stakeholders. Furthermore, the paper examines the application of the futures methodologies in multisectoral urban transitions apart from transportation and draws conclusion on what can be learnt from it.

Abstract

This research intends to illuminate the concept and application of the public policy named fare -free public transport (FFPT), using the cases of Avesta and Tallinn and analysing future applicability of it in the cases of Luxembourg and Uppsala city. The analysis explores the fare-free public transport policy and the theory of sustainable transport. The study presents the different benefits of the policy and its limitations, and how the FFPT is connected to sustainable transport and sustainable development theories and application. Through a case study analysis based in literature review, the analysis of both cities wants to elucidate the application of the FFPT as one important policy tool within cities both for the environment and for the people, and how the policy can develop in the future. Considering this, the presented research also opens the possibility of expansion of the policy to other cities and countries.

Abstract

The transport sector is responsible for a significant and growing proportion of greenhouse gas emissions.  The urgent actions are required to take in the transport sector facing the challenge of growing global change. The major trends, including global urbanization, widespread application of digital technologies, and broad demand for sustainable development, have provided new opportunities for data-driven smart mobility in the future. This research aims to explore potentials of data-driven smart mobility in achieving Sustainable Development Goal 11.2, “provide access to safe, affordable, accessible and sustainable transport systems for all,” and Sustainable Development Goal 13.2, “take urgent action to combat climate change and its impacts” and “integrate climate change measures into national policies, strategies and planning” reducing greenhouse gas emissions every year. In order to meet this aim, this research explores the understandings and innovations of data-driven smart mobility in achieving decarbonization in urban, as well as barriers during the current practices. Hangzhou, as the capital city in Zhejiang Province in China, has been selected for the case study to examine data-driven smart mobility approaches. The research results show that the potentials of the data to tackle climate issues lie in the efficient transport operation and travel behaviors change. Data technologies have been widely applied to improve the integration of travel modes and the efficiency of transport management to reduce greenhouse gas emissions in road traffic. However, there are few drivers to mine data resources for travel behavior change. Moreover, data-driven smart mobility initiatives applied in urban areas involve multiple stakeholders but with limited access to data sharing and opening. Considering disruptive effects and potential promises brought by the big data technologies, the implementation of smart mobility requires for public data strategy with a holistic view of the complex urban challenges and global climate change.