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• Proposing a framework to analyze emission patterns of buses and changes in post-COVID-19. • 2056 buses with 1.5 million ridership and 7589 taxis with 0.2 million trips are used for analysis. • 224 social surveys are collected and show a 56.3% ridership reduction in post-COVID-19. • We find buses cannot be "greener" travel modal than cars if ridership reduces by more than 40%. Emission benefits of transit buses depend on ridership. Declines in ridership caused by COVID-19 leads uncertainty about the emission reduction capacity of buses. This paper provides a method framework for analyzing spatio-temporal emission patterns of buses in combination with real-time ridership and potential emission changes in the post-COVID-19 future. Based on GPS trajectory and Smart Card data of 2056 buses from 278 routes covering 1.5 million ridership in Qingdao, China, spatio-temporal emissions characteristics of buses are studied. 7589 taxis with 0.2 million passengers' trips are used for acquiring private cars' emissions to evaluate the emissions difference between buses and cars. Empirical results show that the average difference between buses and cars with 2 persons can reach up to 117 g/km-person during 7:00–8:59 and 115 g/km-person during 17:00–18:59. However, buses have various emission benefits around the city at different periods. A double increase in emissions during non-rush hours can be observed compared with rush hours. 224 online survey data are used to study the potential ridership reduction trend in post-COVID-19. Results show that 56.3% of respondents would decrease the usage of buses in the post-COVID-19 future. Based on this figure, our analysis shows that per kilometer-person emissions of buses are higher than cars during non-rush hours, however, still lower than cars during rush hours. We conclude that when ridership reduces by more than 40%, buses cannot be "greener" travel modal than cars as before. Finally, several feasible policies are suggested for this potential challenge. Our study provides convincing evidence for understanding the emission patterns of buses, to support better buses investment decisions and promotion on eco-friendly public transport service in the post-COVID-19 future. [ABSTRACT FROM AUTHOR]

• Proposing a framework to assess the emission reduction potential of ride-sharing from empirical mobility data. • Proposing a deep learning-based method that shows higher performance than traditional simulation method. • Over 1 million historical individual GPS records in Tokyo area are employed for analysis. • We found that averagely 26.97% of traveling distance can be saved and maximally 84.52% of reduction of CO2 emission. Spreading green and low-consumption transportation methods is becoming an urgent priority. Ride-sharing, which refers to the sharing of car journeys so that more than one person travel in a car, and prevents the need for others to drive to a location themselves, is a critical solution to this issue. Before being introduced into one place, it needs a potential analysis. However, current studies did this kind of analysis based on home and work locations or social ties between people, which is not precise and straight enough. Few pieces of research departed from real mobility data, but uses time-consuming methodology. In this paper, we proposed an analysis framework to bridge this gap. We chose the case study of Tokyo area with over 1 million GPS travel records and trained a deep learning model to find out this potential. From the computation result, on average, nearly 26.97% of travel distance could be saved by ride-sharing, which told us that there is a significant similarity in the travel pattern of people in Tokyo and there is considerable potential of ride-sharing. Moreover, if half of the original public transit riders in our study case adopt ride-sharing, the quantity of CO 2 is estimated to be reduced by 84.52%; if all of the original public transit riders in our study case adopt ride-sharing, 83.56% of CO 2 emission reduction can be expected with a rebound effect because of increase of participants from public transit. Ride-sharing can not only improve the air quality of these center business districts but also alleviate some city problems like traffic congestion. We believe the analysis of the potential of ride-sharing can provide insight into the decision making of ride-sharing service providers and decision-makers. [ABSTRACT FROM AUTHOR]

• Proposing a framework for assessing fuel consumption of taxi-sharing. • Proposing a novel dispatch system to improve taxi operation efficiency. • Routing probability model integrated to plan flexible and efficient shared trips. • Case study in Shanghai with over 43 million GPS records conducted for analysis. • Result found that taxi-sharing may increase fuel consumption in high demand areas. With the emergence of big geospatial data and the breakthrough of massive data processing, taxi-sharing offers the public a novel transportation mode with high comfort but low cost. However, designing a taxi-sharing system to effectively allocate taxi resources and provides high public acceptance services is an urgent problem to be solved. Furthermore, to what extent the taxi-sharing can be an eco-friendly service without bringing extra pressure to urban emission, fuel consumption, and transportation system is still an unanswered question. This paper proposes a methodology framework to design a taxi-sharing system with driver routing probability based matching and dispatching algorithms. The methodology is capable of matching multiple taxi trips into a sharing trip, with consideration of temporal and spatial feasibilities. The matching of sharing trips includes the determination of which trips to match and the sequence of the destinations. To examine the potential of operation efficiency improved and fuel consumption reduced in taxi-sharing, three scenarios are proposed with different constraints, representing different operation strategies. The sharing trips are then dispatched to the taxis. The potential of operating performance improvement and the potential of fuel consumption reduction are analyzed in the three scenarios. It is found that the delivery part of taxi-sharing may produce more travel distance because of the detour. The key factor for taxi-sharing service to reduce Vehicle Kilometres Travelled is the idle trips and the taxi resources saved. Considering both delivery trips and idle trips together, although taxi-sharing can reduce total fuel consumption in the city, it may increase traffic pressure in certain range area, especially in the key road sections or intersections in the urban road network and the area with high traffic demand. [ABSTRACT FROM AUTHOR]

• Developing a framework to estimate solar PV potential of urban fleet-wide electric buses. • Publicly street-view panoramas, GPS trajectory data and DEM data are used as input. • A case study of Qingdao, China with 547 bus routes, 28,661 street-view panoramas is studied. • Benefits under different driving conditions and operation schedules are evaluated. Transforming the road public transport to run on renewable energy is vital solution to achieve carbon neutral and net zero goals. This paper evaluates the potential of using solar radiation-generated electricity as an auxiliary power supplementary for the battery of electric buses, based on a developed framework that using publicly street-view panoramas, GPS trajectory data and DEM data as input parameters of solar radiation model. A case study of Qingdao, China with 547 bus routes, 28,661 street-view panoramas shows that the solar-radiation electricity generated at noon during the operation accounts for about one-fifth, one-eighth of the total electricity consumption of a bus traveling one kilometer in a sunny day and a cloudy day, respectively. Spatial variability shows significant solar-radiation power generation advantages in newly-launched areas and expressway. The solar power generated in a sunny day can make a bus half of passengers and with air conditioner off at least one extra trip in 2:1 replacement schedule, and nearly close to one extra trip in 4:3 replacement schedule. A correlated relation between the solar-radiation power generation benefit and the operation schedule of electric buses is observed, implying that the high cost of 2:1 replacement schedule for long-distance routes during summer or winter can be reduced. The proposed framework can help us evaluate and understand the feasibility of solar radiation-generated electricity energy of electric bus fleets covering the large-scale urban areas at different times, locations, and weather conditions, so as to support effective decisions at better planning of PV-integrated electric buses. [ABSTRACT FROM AUTHOR]