The impact of metropolitan,county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics

Many municipalities in the U.S. pursue compact development to reduce greenhouse gas (GHG) emissions from driving. Despite the efforts, however, recent studies suggest that some land use strategies such as densification and mixed-use development may result in slower vehicle movements, and consequently generate more driving emissions. Since vehicle miles of travel (VMT) is only a proxy and not an exact measure of emissions, reduction in VMT may not lead to a proportional reduction in transportation GHG emissions. Aside from local land use efforts, regional factors also influence vehicle travel and associated emissions.This study investigates the relationship between land use, vehicle travel, and driving emissions in the selected U.S. metropolitan areas at multiple geographic levels. The study employed structural equation modeling (SEM) techniques to examine how land use influences vehicle travel characteristics and associated emissions. The main data sources for the analyses include the 2009 National Household Travel Survey (NHTS) add-on samples and the Smart Location Database (SLD) from the U.S. Environmental Protection Agency (EPA). The study results show that VMT reduction and the associated environmental benefit do not show a one-on-one relationship due to the emissions penalty of lowered vehicle operating speed. Vehicle travel and associated emissions are not only influenced by local urban form factors but also affected by the greater geographical context.     

A method for the estimation of greenhouse gas emissions based on road geometric design and its application to South Korea

South Korea has the tenth highest greenhouse gas (GHG) emissions worldwide, of which 16% originates from the road sector. Existing estimation methods of road GHG emissions have various limitations, such as low accuracy or the ability to only estimate GHG emissions within a limited area. Therefore, this study aimed to develop a methodology to estimate GHG emissions while considering various geometric designs of roads, including both vertical and horizontal alignment. The developed method is more objective and reliable than existing methodologies that consider only vertical alignment. First, Lamm's theory on travel speed profiles was applied to predict GHG emissions. Then, this study attempted to overcome the limited spatial estimation capacity of existing methods by considering upstream and downstream geometric design parameters simultaneously. Second, this study used the GHG operation mode extracted from the MOtor Vehicle Emission Simulator (MOVES), a modeling system that estimates emissions for mobile sources at the national, county, and project levels for criteria air pollutants, GHGs, and air toxicity. The operation mode includes vehicle type, fuel, and other factors, and is designed to estimate GHG emissions at 1-s intervals. Based on the results of the analysis, the effectiveness of the new method was compared to existing methods using an economic analysis (e.g., cost–benefits from the reduced emissions). This study presents a method for performing sensitive estimations of GHG emissions according to the geometric design of roads, which can be used to collect more accurate data on GHG emissions.     

Greenhouse gas emissions from flying can offset the gain from reduced driving in dense urban areas

Numerous studies have illustrated how denser urban forms lead to smaller greenhouse gas (GHG) emissions from passenger transport. Many of these studies have excluded aviation since the association between urban structure and air travel is not as intuitive as it is the case of ground travel. However, several recent studies have concluded that air travel is a significant contributor to the GHGs from passenger transport. Furthermore, even air travel habits depend heavily on lifestyles and socio-economic factors that are related to the urban form. Here we analyse the interactions between urban structure and different transportation modes and their GHG impacts in Finland. The study utilises the data from the Finnish Transportation Agency’s passenger traffic survey from May 2010 to May 2011, which includes over 12 000 people and over 35 000 trips. The survey is based on one-day travel diaries and also includes additional data on long-distance trips from a longer period. Methodologically, the study takes a traveller’s perspective to assess the GHG emissions from passenger transport. We found that (1) air travel breaks the pattern where GHG emissions decrease with increasing density of urban structures, and (2) in the metropolitan region there is a clear trade-off between car-ownership and air travel in the middle income class. The main policy implication of our study is that air travel must be included in GHG assessments and mitigation strategies targeting travel behaviour. In dense urban regions, the emissions of air travel have the potential to offset the gain from reduced private driving.     

Greenhouse gas impacts of different modality style classes using latent class travel behavior model

This study analyzed the interconnections between urban structure and socioeconomic, demographic and lifestyle variables and direct ground transport greenhouse gas (GHG) emissions in the Helsinki metropolitan region in Finland by using a latent class choice model (LCCM). The aim of the study was to identify and improve our understanding of the latent modality styles which guide people's everyday travel choices, and the resulting GHG implications. The GHG implications for different modality style groups are particularly interesting, since such analysis has not been included in previous studies. This study used the transport survey of the Helsinki Region Transport (HSL) from 2012, including over 17,000 trips, and consisted of two parts: first, the population was divided into classes based on latent class analysis, and secondly, the mode choices and GHG emissions were modelled for each class. Seven modality style groups were defined with strongly varying GHG impacts and travel profiles. According to the class specific choice modelling the probabilities of selecting different modes also varied significantly. The study offers new information for designing effective mitigation policies for different types of modality style groups. For example, car-oriented groups would benefit from more fuel-efficient vehicles and vehicles with alternative power sources, whereas the multimodal traveler could be more receptive to policies promoting cycling and public transport. Overall, the study depicts the potential of the latent class method to study the emissions caused by heterogeneous populations and to search for efficient GHG mitigation possibilities.     

Choice behavior of tourism destination and travel mode: A case study of local residents in Hangzhou,China

The social and economic growth as result of promoting the rapid development of tourism in China has brought tremendous pressure on the urban transportation systems. Research of travel behavior concerning the characteristics of tourists has provided effective information for transportation planning. Due to different city plans, public transportation system design, car parking design and management, etc., the local situation in developed countries differs from the counterpart in China. However, little research has studied the factors influencing the choice of travel destinations in tourism. The research aims to study the tourism destination and mode choice behavior of tourists and provides suggestions to improve tourism transportation service system. An online questionnaire survey is used to collect data including the travel characteristics and personal attributes of local tourists in different holidays in Hangzhou, China. A multinomial logit model is constructed with the trip destination set as the dependent variable. Results show that age, residential type, car ownership, companion type and holiday length have a significant impact on destination choice. To determine what influences modal choice for such trips, a second logit model is established with travel mode set as the dependent variable with the explanatory variables of age, gender, companion type, car ownership, holiday length and travel destination found to be significant. The results demonstrated that people aged 26 to 44 prefer suburban areas, and they are the main group driving to their travel destination. Public transport use frequency decreases when the destination is located outside of the main tourist area. Finally, suggestions have been proposed to mitigate the congestion and parking problem based on model analysis from the perspective of the bus line setting, transfer improvements, and the policy to limit cars, respectively.     

Land-use and socio-economics as determinants of traffic emissions and individual exposure to air pollution

This paper presents a modeling framework developed for the City of Montreal, Canada, and is intended to quantify two indicators that can explain the spatial distribution of traffic-related air pollution at a metropolitan level. The indicators are estimated at the level of the traffic analysis zone (TAZ) and include: (1) the average level of emissions generated per individual and (2) the level of emissions occurring in a zone as a proxy for air pollution exposure. A regional traffic assignment model is extended with capabilities for emission modeling at an individual trip level while taking into account vehicle (type and age) and trip attributes (road type, speed, and volume). We observe that individuals who generate higher emissions from travel tend to reside in areas with lower exposure to traffic emissions while individuals associated with low levels of travel emissions (e.g. travel smaller distances, conduct less trips, and use alternative modes) reside in areas with high levels of traffic pollution. A regression analysis of the two indicators against a set of land-use and socio-economic variables shows that generated emissions per individual are positively associated with car ownership and larger vehicles, while being negatively associated with ownership of newer vehicles, and location in dense and walkable neighborhoods with high levels of commercial land-use. Meanwhile, exposure to emissions is positively associated with dense and walkable neighborhoods and negatively associated with car ownership and larger vehicles. These findings indicate major inequities in the generation of and exposure to traffic-related air pollution.     

Teen travel in the Greater Toronto Area: A descriptive analysis of trends from 1986 to 2006 and the policy implications

This paper extends research on urban form and travel behavior beyond adult travel by examining teen travelers aged 13–19 in the Greater Toronto Area. Data from the Transportation Tomorrow Survey (TTS) survey are used to study four main research questions: (1) How has teen mode choice changed from 1986 to 2006? (2) How do these choices vary as teens transition from the 13–15 age group to being of driving age (16–19)? (3) How do these choices vary across the different urban and suburban regions of the GTA? (4) What are some of the differences between teen travel and adult travel? Results show that in general, active transportation has decreased, while auto-passenger mode shares have increased across the region. The younger group walks more and the older group takes transit more for both school and discretionary travel. Jurisdictions with better transit supply and orientation have higher transit mode shares for school trips, but discretionary trips have very low transit mode shares. Walk mode shares for both school and discretionary travel are similar across all jurisdictions, regardless of whether they are urban or suburban. In contrast to adult travel in the GTA, built form characteristics and transit supply do not appear to have a direct relationship with teen mode choice. Urban form appears to exert an indirect influence on teen travel.     

Residential dissonance and mode choice

Residential dissonance refers to the mismatch in land-use patterns between individuals’ preferred residential neighbourhood type and the type of neighbourhood in which they currently reside. Current knowledge regarding the impact of residential dissonance is limited to short-term travel behaviours in urban vs. suburban, and rural vs. urban areas. Although the prevailing view is that dissonants adjust their orientation and lifestyle around their surrounding land use over time, empirical evidence is lacking to support this proposition. This research identifies both short-term mode choice behaviour and medium-term mode shift behaviour of dissonants in transit oriented development (TODs) vs. non-TOD areas in Brisbane, Australia. Natural groupings of neighbourhood profiles (e.g. residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility levels) of 3957 individuals were identified as living either in a TOD (510 individuals) or non-TOD (3447 individuals) areas in Brisbane using the TwoStep cluster analysis technique. Levels of dissonance were measured based on a factor analysis of 16 items representing the travel attitudes/preferences of individuals. Two multinomial logistic (MNL) regression models were estimated to understand mode choice behaviour of (1) TOD dissonants, and (2) non-TOD dissonants in 2009, controlling for socio-demographics and environmental characteristics. Two additional MNL regression models were estimated to investigate mode shift behaviour of (3) TOD dissonants, and (4) non-TOD dissonants between 2009 and 2011, also controlling for socio-demographic, changes in socio-demographic, and built environmental factors. The findings suggest that travel preference is relatively more influential in transport mode choice decisions compared with built environment features. Little behavioural evidence was found to support the adjustment of a dissonant orientation toward a particular land use feature and mode accessibility they represent (e.g. a modal shift to greater use of the car for non-TOD dissonants). TOD policies should focus on reducing the level of dissonance in TODs in order to enhance transit ridership.     

Potential performance of urban land use and transport strategies in reducing greenhouse gas emissions: Khon Kaen case study,Thailand

ABSTRACT

Transport activities are a key contributor to greenhouse gas (GHG) emissions, global warming, and climate change. In Thailand, private cars are the second largest generator (after trucks) of GHG emissions from the transport sector. This article presents an analysis and evaluation of the implementation of land use and transport measures for reducing GHG emissions in the road network of the Khon Kaen University (KKU) area in Khon Kaen, Thailand. This research applied a bottom-up method to estimate the baseline GHG emissions for several scenarios by adopting the Clean Development Mechanism 2 (CDM2) and Pollution Control Department (PCD) methods over a 20-year planning horizon. The cleaner technology strategy clearly showed the greatest performance in reducing the GHG emission, followed by land use planning and restriction of private vehicle usage. The public transit improvement strategy illustrated the least GHG emissions reduction. Integrated scenarios clearly illustrated larger potential benefits, more effective than the individual scenarios. For both individual and integrated scenarios, the potential performances of the GHG emissions reduction estimated by the PCD method were greater than those assessed by the CDM2 method.     

Determinants of travel mode choice for seeking healthcare: A comparison between elderly and non-elderly patients

People's travel mode choices can vary significantly by age group due to different influencing factors, but relevant research on health-related travel is scarce. In this study, we explored and compared the determinants of travel mode choice for healthcare-seeking non-elderly and elderly patients in Beijing, China. A multinomial logit model was used to analyze data from a recent healthcare-seeking behavior survey. The results show that increased age discourages car use and slightly prompts non-motorized travel in the non-elderly, but has the opposite effect in the elderly group. Household income has a negative effect on non-motorized travel in the non-elderly, but a positive effect in elderly patients. Highly mixed land use, intensive urban development, and difficulty in parking discourage non-elderly patients from traveling by car, but none of these factors have a significant effect on the elderly. Our findings shed light on the unique transportation demands for different age cohorts and inform the creation of age-specific interventions to improve overall access to health.     

Spatial and socio-demographic determinants of South East Queensland students’ school cycling

The low prevalence of Australian students’ utilitarian school cycling could be attributed to the varied and context specific demographic, socio-economic and spatial school travel mode choice determinants. Travel distance is universally important for school cycling and is reliant amongst related home and school spatial proximity factors on a student’s choice of schools. This paper, primarily based on school students’ travel data extracted from the 2009 South East Queensland Household Travel Survey (SEQHTS), examines comparative school cycling travel patterns, school catchment choices and the significant analytical determinants of cycling mode choices from within an urban regional Australian context. Students’ choice of a school external to that located within their designated State school catchment zone was associated with household attributes of parent/guardian employment location, number of income earners and ownership of private vehicles coupled with State school and catchment attributes. Noteworthy variations in school travel distances and modal splits were allied with school catchment choices. Adolescent male students from two parent households owning fewer than two cars and more than two bicycles, with parents/guardians commuting using non-motorised travel modes and resident in Census Collection Districts with conducive cycling environments, contributed largely to the one-way bi-directional primary and secondary school cycling mode shares. This prevalent student cyclist profile indicates the need for enhancements in student school cycling participation, through policies addressing both the spatial (built) and social environment which impact students’ personal and traffic safety coupled with utilitarian cycling image enhancements. Concerted efforts to bolster cycling amongst student segments with current low cycling participation inclusive of females, students from single parent households and those with adequate access to private motorised travel modes may be necessary to further enhance school cycling mode shares. The paper makes a case for individualised targeted travel interventions informed by segregated mode choice determinant analysis for respective primary and secondary school types and directions of school travel.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

Disentangling the behavioural side of the first and last mile problem: the role of modality style and the built environment

The first and last mile (FLM) problem, namely the poor connection between trip origins or destination and public transport stations, is a significant obstacle to sustainable transportation as it is likely to encourage the use of cars for FLM travel, if not for the entire trip. This study examines the role of modality style and built environment in FLM mode choice behaviour, in order to identify the key features that might invoke a travel mode shift from cars to more sustainable travel options for both mandatory and discretionary trips. More specifically, this study draws on disaggregate data from the South East Queensland household travel survey and presents a latent class choice model to unravel modality style groups. Results reveal two distinct individual-level modality style groups: (1) driving and walking oriented; (2) multimodal travellers. Individuals in the second modality style group were found to be relatively inelastic to FLM travel time for mandatory trips, while individuals in the first group were largely unaffected by built environment characteristics and highly habitual in their mode choice behaviour for both mandatory and discretionary trips. Home residence environments with high road intersection density and public transport accessibility, and home residence environments with diverse land use mix, respectively encourage individuals within the second modality style to walk for mandatory trips, and discretionary trips. To this end, when place-based policies seek to change certain built environment features, individuals in the second modality style are more likely to shift their preference from cars to more sustainable modes. Finally, our findings have practical planning implications in targeting mode shift through highlighting the importance of considering the intersection of individual modality style in a given locale and mode choice behaviour. More specifically, our findings advocate for place-based policies that seek to target particular locales with the certain modality style deemed to be more predisposed to adopting a mode shift.     

The role of airport proximity on warehouse location and associated truck trips: Evidence from Toronto,Ontario

This paper examines the two-way relationship between land use and transportation from the perspective of warehouses in the Toronto Census Metropolitan Area. A location choice model is first developed to reproduce the decision process of firms selecting suitable locations to operate warehousing facilities. The results highlight that transportation plays a prominent role in the location of warehouses with proximity to airport, highway infrastructure, and rail to a lesser extent. However, the proportion of industrial land use provides the largest role in the model suggesting that available land and zoning is the most important factor. This paper also studies the impact of warehouse location on freight transportation trips. The resulting analysis highlights that GPS derived trips arising from warehouses near a major airport in Toronto tend to travel 1.8 times further than trips pertaining to other warehouses in the region. This suggests that trips related to the airport are more likely to be connected to a larger supply chain process.     

Mode choice in commuting and the built environment in México City. Is there a chance for non-motorized travel?

Non-motorized transportation (NMT) has emerged as a mitigating alternative for the negative externalities of motorized travel. This research presents an overview of the intra-metropolitan geography of transportation mode choice in the journey to work in the México City Metropolitan Area (MCMA), which can be seen as a representation of the huge socioeconomic inequalities typical of the Global South. The regression model applied showed that, as expected, socioeconomic variables were strong determinants of mode choice. An increase in age, as well as lower categories of socioeconomic class and educational attainment, were associated with the use of transit and non-motorized travel. Other factors positively associated with bike use were distance to the center, density of mass-transit systems stations, street intersection density, and the flat surface. The pattern of walk commuting with respect to the city center followed a u-shaped curve, while factors significantly positively associated were female, population density, the jobs-housing ratio at the origin, and the density of mass-transit systems stations. The paper concludes with a discussion of the research implications to leverage public policy efforts to promote NMT.     

Determinants and spatial variability of after-school travel by teenagers

This research work targeted teenagers to investigate after-school travel patterns and factors affecting their modal choice characteristics in Okinawa, Japan, where teenagers are not allowed to drive. The analysis is based on the cross-sectional data collected for discrete choice modeling of students’ travel in the prefecture. In this study, high school students’ trips from school to home have been analysed using a multinomial logit model. This has revealed the impact of individual, modal, and spatial variables on the mode choice decisions and return trip patterns. A comparative analysis made of downtown and suburb schools exposed differences in travel patterns induced by spatial factors and some existing constraints in modal choice options.     

The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the U.S.

Vehicle ownership is an important determinant of the travel demand forecasting process. Vehicle ownership models are used by policy makers to identify factors that affect vehicle miles traveled, and therefore address problems related to energy consumption, air pollution, and traffic congestion. For the conventional travel demand forecasting, it logically follows land use forecasting, before trip generation, which is commonly treated as step one. The most critical limitation of the vehicle ownership models, especially in the conventional process, is that they are often related mainly to sociodemographic variables, not so much to built environmental variables. In this study, by pooling regional household travel survey data from 32 diverse regions (almost 92,000 households) of the U.S., and by controlling for socio-demographic and the built environmental variables, we estimated a vehicle ownership model that contributes to the understanding of vehicle ownership and improves the accuracy of travel demand forecasts. Two main findings of this research are: 1) The number of vehicles owned by a household increases with socio-demographic variables and decreases with almost all of the built environmental variables. For the urban planning and design practices, this finding suggests that car shedding occurs as built environments become more dense, mixed, connected, and transit-served. 2) We used both count regression and discrete choice models, and the results suggest that count regression models have better predictive accuracy. The model developed in this study can be directly used for travel demand modeling and forecasting by metropolitan planning organizations.     

The influence of socioeconomic characteristics,land use and travel time considerations on mode choice for medium- and longer-distance trips

This paper contributes to the limited number of investigations into the influence of the spatial configuration of land use and transport systems on mode choice for medium- and longer-distance travel (defined here as home-based trips of 50 km and over) in the Netherlands. We have employed data from the 1998 Netherlands National Travel Survey to address the question as to how socioeconomic factors, land use attributes, and travel time affect mode choice for medium- and longer-distance travel, and how their role varies across trip purposes: commuting, business, and leisure. The empirical analysis indicates that land use attributes and travel time considerations are important in explaining the variation in mode choice for medium- and longer-distance travel when controlling for the socioeconomic characteristics of travellers.     

Environmental benefits of air–rail intermodality: The example of Madrid Barajas

The environmental impact of transport is a growing issue in transport infrastructure planning. The construction of a high-speed rail station at the Madrid Barajas Airport in Spain is an example of the integration of different transportation modes, with expected environmental benefits. We construct a model to assess modal choice and environmental benefits. The results show that with high-speed rail the number of people choosing air travel and the private car is reduced leading to important environmental benefits: a reduction of close to 5 kg of CO₂ per passenger, or 10% of all emissions on the corridor. Our results also show that increasing the cost of using the private car is picked up by air transport rather than high-speed rail, leading to an increase in total emissions.     

R-Tresis: developing a transport model system for regional New South Wales

This paper sets out a demand modelling framework for the development of a regional transport and land use model system (R-Tresis), to be implemented for New South Wales (Australia). Traditionally, the focus of such a model system has been major metropolitan areas such as Sydney, where we have developed Tresis (Hensher, 2002). Given the growing concern about regional accessibility to many service classes, there is a need for a modelling capability that can be used to prioritize and guide policy decisions in regions that are often described as remote, rural, low density and small town. In developing a framework that is capable of integrating both demand and supply elements of transportation and land use activity, we recognized the challenges in developing primary data sources, and the high likelihood of a reliance on secondary data sources. This suggested an alternative approach to demand modelling that was not dependent on choice models; namely a suite of continuous choice models in which we capture the actual activities undertaken by each mode on both the demand and supply side at high spatial resolution.