Teresa Galvão

Abstract
By 2050, and in the context of decarbonization and carbon neutrality, many companies worldwide are looking for low-carbon alternatives. Transport companies are probably the most challenging due to the continuing growth in global demand and the high dependency on fossil fuels. Some alternatives are emerging to replace conventional diesel vehicles and thus reduce greenhouse gas emissions and air pollutants. One of these alternatives is the adoption of compressed natural gas (CNG). In this paper, we provide a detailed study of the current emissions from the largest bus fleet company in the metropolitan area of Oporto. For this analysis, we used a top-down and a bottom-up methodology based on EMEP/EEA guidebook to compute the CO2 and air pollution (CO, NMVOC, PM2.5, and NOx) emissions from the fleet. Fuel consumption, energy consumption, vehicle slaughter, electric bus incorporation, and the investments made were taken into consideration in the analyses. From the case study, the overall reduction in CO2 emission was just 6.3%, and the emission factors (air pollutants) from CNG-powered buses and diesel-powered buses are closer and closer. For confirming these results and question the effectiveness of the fleet transitions from diesel to CNG vehicles, we analysed two scenarios. The obtained results reveal the potential and effectiveness of electric buses and other fuel alternatives to reduce CO2 and air pollution.

Abstract
The public transport system is responsible for the displacement of a large part of the population, particularly in developing countries. This fact makes it relevant to evaluate the performance of public transport to provide an efficient and effective service. The purpose of this study is to conduct a performance evaluation of the public transport operation in the Metropolitan Region of Fortaleza (MRF), in the State of Ceara, Brazil. The analysis is based on DEA and the Malmquist index, based on three inputs (total operating time, fleet age, and the mileage traveled) and two outputs (fare revenue and number of passengers). Data were obtained through automated fare collection systems (AFCs) that were implemented in the MRF. Although there were no major fluctuations in performance during the analyzed period, the results indicate that the system's performance declined in certain years. In addition, the analysis enables a better understanding of route performance, considering the operating company or the area of operation, which helps to diagnose and comprehend the operation more effectively. By analyzing the operational performance over time, the proposed approach provides an additional contribution by offering a comprehensive overview to the involved stakeholders, fostering decision-making processes based on evidence.

Abstract
Mobile ticketing services allow urban transport passengers to travel in a convenient and easy way, enhancing their travelling experience. In recent years several mobile ticketing services have started to be developed and launched, but there is still a lot to be done in terms of its effectiveness, efficiency and innovation. This paper presents a micro-location mobile ticketing solution based on Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technologies, called Anda. This solution is based on a check-in/be-out scheme and requires the minimum intervention from the passenger. It is really innovative in the urban transport field, as it takes advantage of BLE technology not usually used for this purpose, it is based on a concept of post-billing with a fare optimization algorithm associated and it allows the micro-location of passengers throughout their journeys. This paper details the architecture of the solution and its mode of operation. It also presents the evaluation methodology that was followed during the pilot trial that took place in the Metropolitan Area of Porto (AMP), Portugal, during one year with 140 real passengers. A set of design lessons were identified as a result of the field tests and materialized in five mobile ticketing design dimensions, constituting important contributions to the design of future mobile ticketing services. Anda was commercially deployed in the AMP in 2018 and is used by thousands of passengers every day.

Abstract
The tourism sector has been facing continuous growth. It plays a vital role in countries' economic development, highlighting the need to keep nurturing it by making it easier and more attractive. This paper presents Tourism as a Service - an innovative concept that aims to ease a day in the life of a tourist by integrating services that might be found spread out through separate tools and services, including ticketing in public transport and touristic attractions, route planning, information, among others. First, focus groups were done in order to understand the users' needs regarding the use of a mobile ticketing solution in tourism. The findings from the literature reviewed and the previous step were then prioritized by relevance in a questionnaire sent to potential users, allowing the creation of a medium-fidelity prototype. The validation through usability testing confirmed an interest in the proposed solution. The critical design choices surrounding the proposed solution were discussed along with improvements and further work to be done.

Abstract
This work proposes an architecture to treat georeferenced data from the OpenStreetMap to plan routes. The methodology considers the following steps: collecting data, incorporating data into a data manager, importing data into a data model, executing routing algorithms, and visualizing routes. Our proposal incorporates the following features characterizing each street segment: safety & security, comfort, accessibility, air quality, time, and distance. Routes can be calculated considering any specified weighting system of these features. The outcome of the application of this architecture allows to calculate and visualize routes from georeferenced data, which can support researchers in the study of multi-criteria routes. Furthermore, this framework enhances the OSM data model adding a multi-criteria dimension for route planning.