Well-to-wheel assessment of natural gas vehicles and their fuel supply infrastructures – Perspectives on gas in transport in Denmark

In this paper, potential natural gas and renewable natural gas supply pathways and natural gas vehicles (NGVs) have been selected and evaluated with regards to well-to-wheel energy expended, greenhouse gas (GHG) emissions, and regulated (air pollutant) emissions. The vehicles included in the evaluation are passenger cars, light-duty vehicles (LDVs), and heavy-duty vehicles (HDVs) for road-transport applications, and a short-range passenger vessel for maritime transport applications. The results show that, compared to conventional fuels, in both transport applications and for all vehicle classes, the use of compressed and liquefied natural gas has a 15–27% GHG emissions reduction effect per km travel. The effect becomes large, 81–211%, when compressed and liquefied renewable natural gas are used instead. The results are sensitive to the type and source of feedstock used, the type of vehicle engine, assumed methane leakage and methane slip, and the allocated energy and environmental digestate credits, in each pathway. In maritime applications, the use of liquefied natural gas and renewable natural gas instead of low sulfur marine fuels results in a 60–100% SOx and 90–96% PM emissions reduction. A 1% methane slip from a dedicated LNG passenger vessel results, on average, in 8.5% increase in net GHG emissions.     

Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.     

Is car drivers’ response to congestion charging schemes based on the correct perception of price signals?

This paper deals with the question of whether the capability of car drivers to estimate the cost of a new hypothetical, highly differentiated congestion charge influences their decision to change travel behaviour. The analysis makes use of an integrated choice and latent variable model (ICLV) which merges classic choice models with the structural equation approach (SEM) for latent variables. This hybrid model improves the explanatory power considerably compared with a conventional discrete choice model. The results suggest that charge complexity decreases the resistance in considering behavioural changes. Car drivers tend to avoid a travel option where the price is not known beforehand, a phenomenon known as ambiguity avoidance.     

Analysis of the effect of charging needs on battery electric vehicle drivers’ route choice behaviour: A case study in the Netherlands

Electric travelling appears to dominate the transport sector in the near future due to the needed transition from internal combustion vehicles (ICV) towards Electric Vehicles (EV) to tackle urban pollution. Given this trend, investigation of the EV drivers’ travel behaviour is of great importance to stakeholders including planners and policymakers, for example in order to locate charging stations. This research explores the Battery Electric Vehicle (BEV) drivers route choice and charging preferences through a Stated Preference (SP) survey. Collecting data from 505 EV drivers in the Netherlands, we report the results of estimating a Mixed Logit (ML) model for those choices. Respondents were requested to choose a route among six alternatives: freeways, arterial ways, and local streets with and without fast charging. Our findings suggest that the classic route attributes (travel time and travel cost), vehicle-related variables (state-of-charge at the origin and destination) and charging characteristics (availability of a slow charging point at the destination, fast charging duration, waiting time in the queue of a fast-charging station) can influence the BEV drivers route choice and charging behaviour significantly. When the state-of-charge (SOC) at the origin is high and a slow charger at the destination is available, routes without fast charging are likely to be preferred. Moreover, local streets (associated with slow speeds and less energy consumption) could be preferred if the SOC at the destination is expected to be low while arterial ways might be selected when a driver must recharge his/her car during the trip via fast charging.     

Incorporating refuelling behaviour and drivers’ preferences in the design of alternative fuels infrastructure in a city

The purpose of this article is to present an optimization model to plan the deployment strategy for hydrogen refuelling stations in a city when Origin–Destination (OD) data are not available. This model considers two objectives: to maximize the traffic covered by the selected hydrogen refuelling stations and minimize the average distance of the city’s inhabitants to the nearest hydrogen refuelling station. As OD data are assumed to be unavailable, the clustering of stations in the highest traffic zones is prevented by a new constraint that takes into account information on the distribution of existing conventional refuelling stations. This model is applied to Seville, a city in Southern Spain of about 140 km² with a population of around 700,000. This application uses the results of a survey of more than 200 Sevillian drivers on their current refuelling tendencies, their willingness to use alternative fuel vehicles and their minimum requirements (regarding maximum distance to be travelled to refuel and number of stations in the city) when establishing a network of alternative refuelling stations.     

Does the aviation Emission Trading System influence the financial evaluation of new airplanes? An assessment of present values and purchase options

In this paper we assess the impact of the CO₂ costs for short- and long-haul aircraft based on present values and on purchase options. We evaluate purchase options with a framework developed for real option analysis to estimate the value of flexibility under uncertain kerosene and CO₂ prices. We find an average influence of CO₂ costs on present values of €1.1 million for the short haul plane and €4.1 million for the long-haul plane over the typical lifetime of an airplane. For purchase options, we find a CO₂ influence of €0.43 million for the long-haul plane and a moderate impact for the short-haul plane. The results underline the importance of CO₂ and kerosene costs for long-haul aircraft.     

Impacts of parental gender and attitudes on children’s school travel mode and parental chauffeuring behavior: results for California based on the 2009 National Household Travel Survey

Research has shown that parental attitudes are a significant predictor of children’s active commuting (walking or biking) to school. However, the impact of parental gender on parental attitudes, and the link between parental attitudes and the gender gap in parental chauffeuring behavior have not received much attention. This paper examines these questions by applying discrete choice models to California data from the 2009 National Household Travel Survey while controlling for a wide range of variables characterizing parents, their children, households, schools, and the local built environment. Our results, conveyed via odds ratios, show that mothers are more likely to have higher concerns about traffic volume, which in turn reduces the likelihood that their children will walk or bike to school. Moreover, even though parental attitudes significantly influence parental chauffeuring behavior, their ability to explain the gender chauffeuring gap is limited. When holding equal concerns, mothers are still more likely than fathers to chauffeur their children to school. Finally, while distance to school and several land use measures (e.g., population density, urbanization level, and percentage of renters) are statistically significant, the impact of an objective measure of walkability is quite small. These results suggest that interventions targeting an increase in children’s walking and biking to school should focus on the concerns of mothers, especially as they relate to traffic characteristics.     

Direct and indirect influences on employed adults’ travel in the UK: New insights from the National Travel Survey data 2002–2010

Recent years saw a continuing shift in labour force composition, e.g. greater participation of women and a prominent rise in part-time workers. There are as yet relatively few recent studies that examine systematically the influences on the travel of employed adults from such perspectives, particularly regarding possible transport disadvantages of the fastest growing segments of workers. A robust analysis requires systematic data on a wide range of explanatory variables and multiple travel outcomes including accessibility, mobility and trip frequency for different trip purposes. The UK NTS data does meet the majority of this demanding data requirement, but its full use has so far been hampered by methodological difficulties. To overcome complex endogeneity problems, we develop novel, integrated structural equation models (SEMs) to uncover the influences of latent land use characteristics, indirect influences on car ownership, interactions among trip purposes as well as residents’ self-selection and spatial sorting. This general-purpose method provides a new, systematic decomposition of the influences on travel outcomes, where the effects of each variable can be examined in turn with robust error terms. The new insights underline two direct policy implications. First, it highlights the contributions of land use planning and urban design in restraining travel demand in the 2000s, and their increasing influence over the decade. Secondly, it shows that there may still be a large mobility disadvantage among the fastest growing segments of workers, particularly in dense urban areas. This research further investigates trend breaking influences before and after 2007 through grouped SEM models, as a test of the methodology for producing regular and timely updates regarding the main influences on personal travel from a system level.     

How much should gasoline be taxed when electric vehicles conquer the market? An analysis of the mismatch between efficient and existing gasoline taxes under emerging electric mobility

The taxation of gasoline is characterized by large variability across countries and recent research has analyzed existing gasoline tax levels from an economic efficiency point of view focusing on conventional internal combustion engine vehicles. Most studies find that existing fuel tax rates do not coincide with economically efficient levels. As long as policymakers do not take action to reduce the resulting efficiency gap, there will be an ongoing welfare loss to the economy. However, the composition of passenger car fleets will probably be subject to fundamental changes in the (near) future due to the emergence of electric mobility. This raises the question of whether the mismatch between current and efficient fuel taxation will persist, shrink, or even exacerbate under emerging electric mobility. This paper aims at answering this question by determining the structure and level of optimal gasoline taxes in the presence of electric vehicles (EVs). First, the optimal (nationwide) gasoline tax is analytically derived employing a general equilibrium approach. It is shown that differences in traffic related marginal external costs among fuel powered cars and EVs affect the corrective Pigouvian component of the optimal gasoline tax while a differential tax treatment influences the fiscal rational of the tax. Second, the model is applied to Germany using differentiated data on e.g. external costs and behavioral responses. Under a wide range of scenarios, the present analyses indicate a strong relationship between optimal gasoline taxes and electric mobility, calling for a downward adjustment of efficient gasoline taxes. The effect is mainly driven by financial incentives for purchasing and using EVs. Since fuel is likely to be undertaxed in many countries, the emergence of electric mobility will therefore close the gap between gasoline taxes in place and economically efficient taxes. On the other side, it will increase the efficiency gap in those countries where gasoline is overtaxed. This also has important implications for policy concerned with environmental objectives. Pushing electric mobility seriously and at the same time taxing gasoline efficiently could actually prevent sufficient CO₂ emission savings. However, at least in the case of Germany, even a downward adjusted optimal gasoline tax under electric mobility is likely to be higher than the current (non-optimal) tax.     

Motorcycle-based adolescents’ travel behaviour during the school morning commute and the effect of intra-household interaction on departure time and mode choice

We hypothesise that intra-household interaction influences home departure time and mode choice for the morning commute. In Indonesia, over 71% of vehicles on the road are motorcycles. This fact increases the significance of household interaction in influencing transport mode choice since the simplicity of the motorcycle allows a great degree of versatility in regard to multiple family member transport. To emphasise this point, our study focuses on the unique travel behaviour of adolescents during the school morning commute which, due to the use of the motorcycle, is a combination of the travel behaviour of accompanied children and escorting adults. Our study discovers that adolescents are likely to shift their school arrival time very early or close to the designated starting time in relation to motorcycle-based parental escort to school. In regard to mode choice, adolescent students prefer to be escorted by motorcycle rather than take public transport.     

Influences of the driver’s bounded rationality on micro driving behavior,fuel consumption and emissions

In this paper, we propose an extended car-following model to study the influences of the driver’s bounded rationality on his/her micro driving behavior, and the fuel consumption, CO, HC and NO_X of each vehicle under two typical cases, where Case I is the starting process and Case II is the evolution process of a small perturbation. The numerical results indicate that considering the driver’s bounded rationality will reduce his/her speed during the starting process and improve the stability of the traffic flow during the evolution of the small perturbation, and reduce the total fuel consumption, CO, HC and NO_X of each vehicle under the above two cases.     

How to Capture the Passengers’ Point of View on a Transit Service through Rating and Choice Options

Abstract

In this paper, a methodology for capturing the transit passenger’s point of view by using both rating and choice options is proposed. For this purpose, some discrete choice logit models are introduced; the models allow the probability of choice of some alternative transit services to be calculated, and the importance of each service aspect to be determined. The models are calibrated by using data collected by a survey in which a stated preferences experiment was proposed to a sample of passengers, and some judgements were expressed by them about their transit services, in terms of perceptions and expectations. The introduced methodology provides a relevant contribution from a practical viewpoint because it allows the identification of the most important aspects on overall service quality; it is useful to the transit operators for measuring service quality and for investing on the various service aspects in order to effectively improve transit services.     

An analysis of children’s leisure activity engagement: examining the day of week, location, physical activity level, and fixity dimensions

This paper presents a detailed analysis of discretionary leisure activity engagement by children. Children’s leisure activity engagement is of much interest to transportation professionals from an activity-based travel demand modeling perspective, to child development professionals from a sociological perspective, and to health professionals from an active lifestyle perspective that can help prevent obesity and other medical ailments from an early age. Using data from the 2002 Child Development Supplement of the Panel Study of Income Dynamics, this paper presents a detailed analysis of children’s discretionary activity engagement by day of week (weekend versus weekday), location (in-home versus out-of-home), type of activity (physically active versus passive), and nature of activity (structured versus unstructured). A mixed multiple discrete-continuous extreme value model formulation is adopted to account for the fact that children may participate in multiple activities and allocate positive time duration to each of the activities chosen. It is found that children participate at the highest rate and for the longest duration in passive unstructured leisure activities inside the home. Children in households with parents who are employed, higher income, or higher education were found to participate in structured outdoor activities at higher rates. The child activity modeling framework and methodology presented in this paper lends itself for incorporation into larger activity-based travel model systems where it is imperative that children’s activity-travel patterns be explicitly modeled—both from a child health and well-being policy perspective and from a travel forecasting perspective.

Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam,The Netherlands

We investigated perceived travel possibilities (or subjective choice-sets, consideration-sets) of car and train travellers on the main corridors to the city of Amsterdam, The Netherlands, and associations with traveller and trip characteristics. We conducted secondary analysis on a survey sample consisting of 7950 train and 19,232 car travellers. Forty-five percent of train travellers had a car in their objective choice-set, 27% of them would however never use it for this trip. Trip destination city centre, trip purpose, paying for the trip, public transport commitment, traffic congestion and parking problems were associated with consideration of car as alternative. Forty-two percent of car travellers had public transport in their subjective choice-set. The ratio between perceived public transport and objective car travel time stood out as determinant of consideration-sets, next to destination city centre, trip purpose, travel time and private versus company car ownership. On average, car travellers’ perceptions of public transport travel time exceeded objective values by 46%. We estimated that if perceptions would be more accurate, two out of three car travellers that currently do not see public transport as an alternative would include it in their choice-set, and use it from time to time. This effect has strong theoretical and policy implications.     

Investigating the impacts of weather variability on individual’s daily activity–travel patterns: A comparison between commuters and non-commuters in Sweden

Understanding travel behaviour change under various weather conditions can help analysts and policy makers incorporate the uniqueness of local weather and climate within their policy design, especially given the fact that future climate and weather will become more unpredictable and adverse. Using datasets from the Swedish National Travel Survey and the Swedish Meteorological and Hydrological Institute that spans a period of thirteen years, this study explores the impacts of weather variability on individual activity–travel patterns. In doing so, this study uses an alternative representation of weather from that of directly applying observed weather parameters. Furthermore, this study employs a holistic model structure. The model structure is able to analyse the simultaneous effects of weather on a wide range of interrelated travel behavioural aspects, which has not been investigated in previous weather studies. Structural equation models (SEM) are applied for this purpose. The models for commuters and non-commuters are constructed separately. The analysis results show that the effects of weather can be even more extreme when considering indirect effects from other travel behaviour indicators involved in the decision-making processes. Commuters are shown to be much less sensitive to weather changes than non-commuters. Variation of monthly average temperature is shown to play a more important role in influencing individual travel behaviour than variation of daily temperature relative to its monthly mean, whilst in the short term, individual activity–travel choices are shown to be more sensitive to the daily variation of the relative humidity and wind speed relative to the month mean. Poor visibility and heavy rain are shown to strongly discourage the intention to travel, leading to a reduction in non-work activity duration, travel time and the number of trips on the given day. These findings depict a more comprehensive picture of weather impact compared to previous studies and highlight the importance of considering interdependencies of activity travel indicators when evaluating weather impacts.     

A comment on W. Wei and M. Hansen’s benefit estimation in “An aggregate demand model for air passenger traffic in the hub-and-spoke network”

This comment analyzes the demand model and method used by W. Wei and M. Hansen for computing the benefits of an airport capacity extension. The log-linear specification and coefficients of the demand function imply that the airport extension’s positive effect on demand decreases with the volume of traffic and associated congestion. If this unlikely result is accepted, the surplus method used by Wei and Hansen underestimates the users’ investment benefit. The note argues that the marginal willingness to pay for a capacity extension should rather increase with congestion. If this is the case, the method used by Wei and Hansen could actually overestimates the benefit.A better specification would rather allow for a function concave to the origin in order to account for capacity constraints, and also set a maximum finite price. Above all, a fair evaluation of the users’ benefit should be based on a function which explicitly includes a variable, or function of variables, that permits an estimation of the users’ cost of congestion.