Urban form,commuting patterns and CO2 emissions: What differences between the municipality’s residents and its jobs?

This article investigates the links between urban form and commuting patterns, and the CO₂ emissions associated with them, in the municipalities that comprise the New Town of Marne-la-Vallée (NTMV) located in the Paris Region. The paper distinguishes between the commutes performed by residents and those generated by the jobs located in a municipality. The contribution of the paper is twofold. Firstly, it shows that the CO₂ emissions of commutes differ greatly depending on whether one considers residents or jobs: hence focusing on the travel behaviour of residents can lead to significant errors in the assessment of the CO₂ emissions generated by a municipality, and therefore its environmental sustainability. Secondly, the paper explores the relationship between commuting trips and several indicators of urban form: density, compactness, jobs-to-residents ratio, accessibility to public transport and distance from Paris. We highlight that high jobs-to-residents ratios tend to increase the proportion of jobs held by residents. Density and compactness are associated with more sustainable travel behaviour among residents, but not non-residents. Finally, the shape of the public transport system, which mainly connects the municipalities of the NTMV with Paris, tends to decrease the proportion of jobs held by residents, especially in the municipalities that are close to Paris, and does not allow non-residents, most of whom do not travel from Paris, to use public transport.     

Exploring transport carbon futures using population microsimulation and travel diaries: Beijing to 2030

Evaluating transport policy for cities in developing countries is often constrained by data availability that limits the use of conventional appraisal models. Here, we present a new ‘bottom-up’ methodology to estimate transport CO₂ emission from daily urban passenger travel for Beijing, a megacity with relatively sparse data on travel behaviour. A spatial microsimulation, based on an activity diary survey and two sample population censuses, is used to simulate, for Beijing’s urban districts, a realistic synthetic population, and their daily travel and CO₂ emission over 2000–2010. This approach provides greater insight into the spatial variability of transport CO₂ emission than has previously been possible for Beijing, and further, enables an examination of the role of socio-demographics, urban form and transport developments in contributing to emissions over the modelled period.Using the 2000–2010 CO₂ emission estimates as a baseline, CO₂ emissions from passenger travel are then modelled to 2030 under scenarios exploring politically plausible strategies on transport (public transport infrastructure investment, and vehicle constraint), urban development (compaction) and vehicle technology (faster adoption of clean vehicle technology). The results showed that, compared to the trend scenario, employing both transport and urban development policies could reduce total passenger CO₂ emission to 2030 by 24%, and by 43% if all strategies were applied together. The study reveals the potential of microsimulation in emission estimation for large cities in developing countries where data availability may constrain more traditional approaches.     

Impact of public transport and non-motorized transport infrastructure on travel mode shares,energy, emissions and safety: Case of Indian cities

Current modal share in Indian cities is in favor of non-motorized transport (NMT) and public transport (PT), however historical trends shows decline in its use. Existing NMT and PT infrastructure in Indian cities is of poor quality resulting in increasing risk from road traffic crashes to these users. It is therefore likely that the current NMT and PT users will shift to personal motorized vehicles (PMV) as and when they can afford it. Share of NMT and PT users can be retained and possibly increased if safe and convenient facilities for them are created. This shall also have impact on reducing environment impacts of transport system.We have studied travel behavior of three medium size cities – Udaipur, Rajkot and Vishakhapatnam. Later the impact of improving built environment and infrastructure on travel mode shares, fuel consumption, emission levels and traffic safety in Rajkot and Vishakhapatnam are analyzed. For the purpose three scenarios are developed – improving only NMT infrastructure, improving only bus infrastructure and improving both NMT and bus infrastructure.The study shows the strong role of NMT infrastructure in both cities despite geographical dissimilarities. The scenario analysis shows maximum reduction in CO₂ emissions is achieved when both PT and NMT infrastructure are improved. Improvement in safety indicator is highest in this scenario. Improving only PT infrastructure may have marginal effect on overall reduction of CO₂ emissions and adverse effects on traffic safety. NMT infrastructure is crucial for maintaining the travel mode shares in favor of PT and NMT in future.     

Policy packages for modal shift and CO2 reduction in Lille,France

This paper proposes different policy scenarios to cut CO₂ emissions caused by the urban mobility of passengers. More precisely, we compare the effects of the ‘direct tool’ of carbon tax, to a combination of ‘indirect tools’ – not originally aimed at reducing CO₂ (i.e. congestion charging, parking charges and a reduction in public transport travel time) in terms of CO₂ impacts through a change in the modal split. In our model, modal choices depend on individual characteristics, trip features (including the effects of policy tools), and land use at origin and destination zones. Personal “CO₂ emissions budgets” resulting from the trips observed in the metropolitan area of Lille (France) in 2006 are calculated and compared to the situation related to the different policy scenarios. We find that an increase of 50% in parking charges combined with a cordon toll of €1.20 and a 10% travel time decrease in public transport services (made after recycling toll-revenues) is the winning scenario. The combined effects of all the policy scenarios are superior to their separate effects.     

Estimating changes in transport CO2 emissions due to changes in weather and climate in Sweden

There is a considerable body of studies on the relationship between daily transport activities and CO₂ emissions. However, how these emissions vary in different weather conditions within and between the seasons of the year is largely unknown. Because individual activity–travel patterns are not static but vary in different weather conditions, it is immensely important to understand how CO₂ emissions vary due to the change of weather. Using Swedish National Travel Survey data, with emission factors calculated through the European emission factor model ARTEMIS, this study is a first attempt to derive the amount of CO₂ emission changes subject to the change of weather conditions. A series of econometric models was used to model travel behaviour variables that are crucial for influencing individual CO₂ emissions. The marginal effects of weather variables on travel behaviour variables were derived. The results show an increase of individual CO₂ emissions in a warmer climate and in more extreme temperature conditions, whereas increasing precipitation amounts and snow depths show limited effects on individual CO₂ emissions. It is worth noting that the change in CO₂ emissions in the scenario of a warmer climate and a more extreme temperature tends to be greater than the sum of changes in CO₂ emissions in each individual scenario. Given that a warmer climate and more extreme weather could co-occur more frequently in the future, this result suggests even greater individual CO₂ emissions than expected in such a future climate.     

Individual transport emissions and the built environment: A structural equation modelling approach

Increasing CO₂ emissions from the transport sector have raised substantial concerns among researchers and policy makers. This research examines the impact of the built environment on individual transport emissions through two mediate variables, vehicle usage and vehicle type choice, within a structural equation modelling (SEM) framework. We find that new-urbanism-type built environment characteristics, including high density, mixed land use, good connectivity, and easy access to public transport systems help reduce transport CO₂ emissions. Such mitigating effect is achieved largely through the reduced vehicle miles travelled (VMT) and is enhanced slightly by the more efficient vehicles owned by individuals living in denser and more diverse neighborhoods, all else being equal. Our research findings provide some new evidence that supports land use policies as an effective strategy to reduce transport CO₂ emissions.     

Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO₂ footprints by 84% when buying standard consumer electronics products.     

Would personal carbon trading reduce travel emissions more effectively than a carbon tax?

The application of personal carbon trading (PCT) to transport choices has recently been considered in the literature as a means of reducing CO₂ emissions. Its potential effectiveness in changing car travel behavior is compared to the conventional carbon tax (CT) by means of a stated preferences survey conducted among French drivers (N ∼ 300). We show evidence that PCT could effectively change travel behavior and hence reduce transport emissions from personal travel. There is however a definite reluctance to reduce car travel. We were unable to demonstrate any significant difference between the effectiveness of PCT and the CT with regard to changing travel behavior. However, in the experiment, the PCT scheme provided consistent results while this was not the case for the CT scheme. Further research is needed into the “social norm” conveyed by a personal emissions allowance.     

Examining the effects of the built environment and residential self-selection on commuting trips and the related CO2 emissions: An empirical study in Guangzhou,China

Numerous studies have established the link between the built environment and travel behavior. However, fewer studies have focused on environmental costs of travel (such as CO₂ emissions) with respect to residential self-selection. Combined with the application of TIQS (Travel Intelligent Query System), this study develops a structural equations model (SEM) to examine the effects of the built environment and residential self-selection on commuting trips and their related CO₂ emissions using data from 2015 in Guangzhou, China. The results demonstrate that the effect of residential self-selection also exists in Chinese cities, influencing residents’ choice of living environments and ultimately affecting their commute trip CO₂ emissions. After controlling for the effect of residential self-selection, built environment variables still have significant effects on CO₂ emissions from commuting although some are indirect effects that work through mediating variables (car ownership and commuting trip distance). Specifically, CO₂ emissions are negatively affected by land-use mix, residential density, metro station density and road network density. Conversely, bus stop density, distance to city centers and parking availability near the workplace have positive effects on CO₂ emissions. To promote low carbon travel, intervention on the built environment would be effective and necessary.     

Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area

In many countries passenger transport is significantly subsidized in a variety of ways for various reasons. The objective of this paper is to examine efficiency, distributional, environmental (CO₂ emissions) and spatial effects of increasing different kinds of passenger transport subsidies discriminating between household types, travel purposes and travel modes. The effects are calculated by applying a numerical spatial general equilibrium approach calibrated to an average German metropolitan area. In extension to most studies focusing on only one kind of subsidy, we compare the effects of different transport subsidies within the same unified framework that allows to account for two features not yet considered simultaneously in studies on transport subsidies: endogenous labor supply and location decisions. Furthermore, congestion, travel mode choice, travel related CO₂ emissions and institutional details regarding the tax system in Germany are taken into account. The results suggest that optimal subsidy levels are either small or even zero. While subsidizing public transport is welfare enhancing, subsidies to urban road traffic reduce aggregate urban welfare. Concerning the latter it is shown that making investments in urban road infrastructure capacity or reducing gasoline taxes may even be harmful to residents using predominantly automobile. In contrast, pure commuting subsidies hardly affect aggregate urban welfare, but distributional effects are substantial. All policies cause suburbanization of city residents and (except for subsidizing public transport) contribute to urban sprawl by raising the spatial imbalance of residences and jobs but the effect is relatively small. In addition, the policies induce a very differentiated pattern regarding distributional effects, benefits of landowners and environmental effects.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Low-carbon futures for Shenzhen’s urban passenger transport: A human-based approach

Shenzhen, one of China’s leading cities, has the potential to be a model for achieving China’s ambitious CO₂ emission reduction targets. Using data from a travel diary survey in Shenzhen in 2014, we develop a human-based agent model to conduct a scenario study of future urban passenger transport energy consumption and CO₂ emissions from 2014 to 2050. Responses to different policy interventions at the individual level are taken into account. We find that with current policies, the carbon emissions of the urban passenger transport sector in Shenzhen will continuously increase without a peak before 2050. Strengthening 21 transport policies will help Shenzhen to peak the carbon emissions by 2030 for passenger transport. Among these policies, the car quota policy and the fuel economy standard are essential for achieving a carbon peak by 2030. In addition, a package of seven policies, including fewer car quotas, a stricter fuel economy standard, raising parking fees, limiting parking supply, increasing EV charging facilities and subway lines, and improving public transport services, is sufficient to peak carbon emissions by 2030, although at an emissions level higher than for the 21 policies.     

Transportation carbon dioxide emissions by built environment and family lifecycle: Case study of the Osaka metropolitan area

How a city grows and changes, along with where people choose to live likely affects travel behavior, and thus the amount of transportation CO₂ emissions that they produce. People generally go through different stages in their life, and different travel needs are associated with each. The impact of the built environment may vary depending on the lifecycle stage, and the years spent at each stage will differ. A family with children may last for twenty to thirty years, while the time spent without dependents might be short in comparison. Over a family’s lifecycle, how big of a difference might the built environment, through household location choice, have on the amount of transportation CO₂ emissions produced? From a climate change perspective, how significant is residential location on the CO₂ produced by transportation use? This paper uses data from the Osaka metropolitan area to compare the direct transportation CO₂ emissions produced over a family’s lifecycle across five different built environments to determine whether any are sustainable and which lifecycle stage has the greatest overall emissions. This understanding would enable the design of a targeted policy based on household lifecycle to reduce overall transportation CO₂ of individuals throughout one’s lifecycle. The yearly average per-capita family lifetime transportation CO₂ emissions were 0.25, 0.35, 0.58, 0.78, and 0.79 metric tonnes for the commercial, mixed-commercial, mixed-residential, autonomous, and rural areas respectively. The results show that only the commercial and mixed-commercial areas were considered to be sustainable from a climate change and transportation perspective.     

Prediction of vehicle CO2 emission and its application to eco-routing navigation

Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO₂ emission per kilometer and determine an eco-friendly path that results in minimum CO₂ emissions while satisfying travel time budget. The vehicle CO₂ emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO₂ emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO₂ emission. Specifically, the benefit trade-off between CO₂ emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO₂ emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.     

Modeling and forecasting household energy consumption and related CO2 emissions integrating UrbanSim and transportation models: an Atlanta BeltLine case study

Reducing energy consumption and controlling greenhouse gas emissions are key challenges for urban residents. Because urban areas are complex and dynamic, affected by many driving factors in terms of growth, development, and demographics, urban planners and policy makers need a sophisticated understanding of how residential lifestyle, transportation behavior, land-use changes, and land-use policies affect residential energy consumption and associated CO₂ emissions. This study presents an approach to modeling and simulating future household energy consumption and CO₂ emissions over a 30-year planning period, using an energy-consumption regression approach based on the UrbanSim model. Outputs from UrbanSim for a baseline scenario are compared with those from a no-transportation-demand model and an Atlanta BeltLine scenario. The results indicate that incorporation of a travel demand model can make the simulation more reasonable and that the BeltLine project holds potential for curbing energy consumption and CO₂ emissions.     

Can we reduce car use and, if so, how? A review of available evidence

Transport accounts for nearly a quarter of current energy-related carbon dioxide emissions with car travel constituting more than three quarters of all vehicle kilometres travelled. Interventions to change transport behaviour, and especially to reduce car use, could reduce CO₂ emissions from road transport more quickly than technological measures. It is unclear, however, which interventions are effective in reducing car use and what the likely impact of these interventions would be on CO₂ emissions. A two-stage systematic search was conducted focusing on reviews published since 2000 and primary intervention evaluations referenced therein. Sixty-nine reviews were considered and 47 primary evaluations found. These reported 77 intervention evaluations, including measures of car-use reduction. Evaluations of interventions varied widely in the methods they employed and the outcomes measures they reported. It was not possible to synthesise the findings using meta-analysis. Overall, the evidence base was found to be weak. Only 12 of the 77 evaluations were judged to be methodologically strong, and only half of these found that the intervention being evaluated reduced car use. A number of intervention approaches were identified as potentially effective but, given the small number of methodologically strong studies, it is difficult to draw robust conclusions from current evidence. More methodologically sound research is needed in this area.     

Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.

     

Minimizing CO2e emissions by setting a road toll

The main purpose of this paper is to develop a bi-level pricing model to minimize the CO₂e emissions and the total travel time in a small road network. In the lower level of the model, it is assumed that users of the road network find a dynamic user equilibrium which minimizes the total costs of those in the system. For the higher level of the model, different road toll strategies are applied in order to minimize the CO₂e emissions. The model has been applied to an illustrative example. It shows the effects on traffic flows, revenues, total time and CO₂e emissions for different numbers of servers collecting tolls and different pricing strategies over a morning peak traffic period. The results show that the CO₂e emissions produced can be significantly affected by the number of servers and the type of toll strategy employed. The model is also used to find the best toll strategy when there is a constraint on the revenue that is required to be raised from the toll and how this affects the emissions produced. Further runs compare strategies to minimize the CO₂e emissions with those that minimize total travel time in the road system. In the illustrative example, the results for minimizing CO₂e emissions are shown to be similar to the results obtained from minimizing the total travel time.     

Factors and scenario analysis of transport carbon dioxide emissions in rapidly-developing cities

To identify key factors of transport CO₂ emissions and determine effective policies for emission reductions in fast-growing cities, this study establishes transport CO₂ emission models, quantifying the influences of polycentricity and satellite cities and re-examining the effects of per capita GDP and metro service. Based on the model results, we forecast future residents’ urban transport CO₂ emissions under several scenarios of different urban and transport policies and new energy technologies. We find nonlinear quadratic growth relationship between commuting CO₂ emissions and per capita GDP, and the elasticities of household and individual commuting CO₂ emission to per capita GDP are 1.90% and 1.45%, respectively. Developing job-housing balanced satellite cities and self-contained polycentric city can greatly decrease emissions from high emitters and can contribute to about 51–82% of the emission reductions by 2050 compared with the scenario of business as usual (BAU). Promotion of electric vehicles, electric public buses, metros, and improvement of traditional energy efficiency contributes to about 48–57% of the emission reductions by 2050 compared with the BAU. When these policies and technologies are combined, about 90% of the emissions could be reduced by 2050 compared with the BAU, and the emissions will be about 1.2–4.9 times of the present. The findings suggest that fostering polycentric urban form and job-housing balanced satellite cities is the key step for future transport CO₂ emission reductions. Metro network promotion, energy efficiency improvement, and new energy type applications can also be effective in emission reductions.     

A point card system for public transport utilization in Korea

This study analyzes consumer preferences for a new incentive program based on a point card to promote green consumption; the study also examines the program’s impact on bus utilization in South Korea. An ex-ante analysis was conducted to examine how consumer behavior can be modified based on varying incentive levels of the point card system. In addition, the effect of the system on consumers’ public transport utilization and resulting CO₂ emissions reductions are analyzed. The adoption probability of the point card is forecast at about 93%, and annual CO₂ emissions are forecast to decrease by 610 kt CO₂.