Integrated modeling of car/motorcycle ownership, type and usage for estimating energy consumption and emissions

Devising effective management strategies to relieve dependency on private vehicles, i.e. cars and motorcycles, depends on the ability to accurately and carefully examine the effects of corresponding strategies. Disaggregate choice models regarding the ownership, type and usage of cars and motorcycles are required to achieve this. Consequently, this study proposes integrated car and motorcycle models based on a large-scale questionnaire survey of Taiwanese owners of cars and motorcycles, respectively. Incorporating gas mileage and emission coefficients for different types of cars and motorcycles into the proposed models can enable the estimation and comparison of reductions in energy consumption and emissions under various management strategies. To demonstrate the applicability of the proposed integrated models, scenarios involving 10% and 30% increases in gas prices are analyzed and compared. The results indicate that gas price elasticities of cars and motorcycles are low, ranging from 0.47 to 0.50 for cars and 0.11 for motorcycles. Additionally, a high ratio of discouraged car users shifting to use of motorcycles neutralizes the effects of increased gas price in reducing energy consumption and emissions. Pollution of CO and HC even slightly increased because motorcycles are much more polluting in terms of CO and HC. At last, the reductions of energy consumption and emissions under 10% and 30% increase (or decrease) in other manipulating variables are also estimated and compared. The countermeasures for reducing ownership and usage of cars and motorcycles are then recommended accordingly.     

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.     

CO2 emissions and expansion of railway,road, airline and in-land waterway networks over the 1985–2013 period in China: A time series analysis

China, the world’s largest CO₂ emitter, is continuing its long-term strategy to use transportation investments as a tool for development. With the expectation that transportation will contribute 30–40% of the total CO₂ emissions in China in the near future, there is an imminent need to identify how the development of different transportation modes may have different long-term effects on CO₂ emissions. Using time series data over the period of 1985–2013, this paper applies the combined autoregressive distributed lag (ARDL) and vector error correction model (VECM) approach to identify short- and long-run causal relationships between CO₂ emissions and mode-specific transportation development, including railway, road, airline, and inland waterway. We find that China’s domestic expansions of road, airline, and waterway infrastructure lead to long-run increases in CO₂ emissions. Among them, waterway has the strongest positive impact on CO₂ emissions, followed by road. Despite a short-run, positive impact on CO₂ emissions, railway expansion leads to long-run decreases in CO₂ emissions. The results are especially encouraging for the central government of China given its long-standing and on-going efforts to expand railway infrastructure at the national level. Looking forward, it is recommended that China continues its national investments in railway infrastructure to achieve both environment and economy goals.     

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.     

Structural equation modeling for national travel demand: an examination of the relationships between communication modes

This paper examines the relationships among different transportation modes, and between transportation and telecommunications, by applying the structural equation modeling (SEM) technique. For this purpose, we collected and compiled time series data on national travel demand, and socioeconomic and telecommunications conditions in Taiwan, and built national travel demand models using SEM. The estimation results show that the relationship between telecommunications and transportation demand (either car ownership or public transportation) is more complementary than substitutional. Moreover, car ownership is a type of inelastic necessity good, and its relationship with public transportation is more substitutional than complementary. Finally, among the three public transportation modes – rail, bus and domestic air – it is found that air is weakest in terms of competitive power. From the viewpoint of long-term forecasting trends, the bus holds its competitive power in comparison with other public transportation modes and would not be replaced in the future.     

Designing a route planner to facilitate and promote cycling in Metro Vancouver,Canada

With increasing fuel costs, greater awareness of greenhouse gas emissions and increasing obesity levels, cycling is promoted as a health promoting and sustainable transport mode. We developed a cycling route planner (http://cyclevancouver.ubc.ca) for Metro Vancouver, British Columbia, Canada, to facilitate cycling amongst the general public and to facilitate new route location by transportation planners. The geographical information system-based planner incorporates variables that influence choices to travel by bicycle (e.g., distance, elevation gain, safety, route features, air pollution and links to transit) in selecting the preferred routing. Using a familiar and user-friendly Google Maps interface, the planner allows individuals to seek optimized cycling routes throughout the region based on their own preferences. In addition to the incorporation of multiple user preferences in route selection, the planner is unique amongst cycling route planners in its use of topology to minimize data storage redundancy, its reliance on node/vertex index tables to increase efficiency of the route selection process, and the use of web services and asynchronous technologies for quick data delivery. Use of this tool can help promote bicycle travel as a form of active transportation and help lower greenhouse gas carbon dioxide (CO₂) and air pollutant emissions by reducing car trips.     

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.     

Six years of CO2-based tax incentives for new passenger cars in The Netherlands: Impacts on purchasing behavior trends and CO2 effectiveness

There is growing evidence that consumers respond more effectively to upfront price signals, such as vehicle purchase taxes and feebate policies, and to tax incentives that are more salient than others, such as company car taxes graded by CO₂ emissions. This paper examines tax changes in The Netherlands, which are among the most stringent and most salient in Europe, and assesses the ex-post purchasing impacts and CO₂ effectiveness of six years of CO₂-based tax incentives for low-carbon cars in The Netherlands. Dutch tax incentives resulted in 13 g/km, or 11% lower average CO₂ emissions in 2013. The Netherlands has moved from the 12th position before the tax changes in 2007 to become Europe’s number one in terms of the lowest average new car CO₂ emissions and highest share of electric vehicles in 2013. Tax incentives for new cars sold between 2008 and 2013 have resulted in 4.6 million tons of potential lifetime CO₂ abatement at the cost of a drop in tax revenues of 30–50%. However, when corrected for the Dutch policy-induced increasing real-world fuel-economy shortfall and leakage of carbon reduction potential through vehicle export of low-carbon cars, only 3.5 million tons or 75% of the CO₂ reduction remains. CO₂-based tax incentives for company cars seem to have contributed the most to the observed turnaround in purchasing behavior towards lower CO₂-emitting passenger cars.     

Commuters’ behavior towards upgraded bus services in Greater Beirut: Implications for greenhouse gas emissions,social welfare and transport policy

Climate change is one of the most critical environmental challenges faced in the world today. The transportation sector alone contributes to 22% of carbon emissions, of which 80% are contributed by road transportation. In this paper we investigate the potential private car greenhouse gas (GHG) emissions reduction and social welfare gains resulting from upgrading the bus service in the Greater Beirut Area. To this end, a stated preference (SP) survey on mode switching from private car to bus was conducted in this area and analyzed by means of a mixed logit model. We then used the model outputs to simulate aggregate switching behavior in the study area and the attendant welfare and environmental gains and private car GHG emissions reductions under various alternative scenarios of bus service upgrade. We recommend a bundle of realistic bus service improvements in the short term that will result in a reasonable shift to buses and measurable reduction in private car emissions. We argue that such improvements will need to be comprehensive in scope and include both improvements in bus level of service attributes (access/egress time, headway, in-vehicle travel time, and number of transfers) and the provision of amenities, including air-conditioning and Wi-Fi. Moreover, such a service needs to be cheaply priced to achieve reasonably high levels of switching behavior. With a comprehensively overhauled bus service, one would expect that bus ridership would increase for commuting purposes at first, and once the habit for it is formed, for travel purposes other than commuting, hence dramatically broadening the scope of private car GHG emissions reduction. This said, this study demonstrates the limits of focused sectorial policies in targeting and reducing private car GHG emissions, and highlights the need for combining behavioral interventions with other measures, most notably technological innovations, in order for the contribution of this sector to GHG emissions mitigation to be sizable.     

CO2 emissions efficiency and marginal abatement costs of the regional transportation sectors in China

Nowadays, evaluating CO₂ emissions efficiency and its marginal abatement cost in transportation sectors has been a hot topic. However, while evaluating the CO₂ marginal abatement cost using data envelopment analysis approach, the weak disposability of CO₂ may imply positive abatement cost, which undoubtedly violates our common sense. To obtain non-positive marginal abatement cost, CO₂ emissions should be treated as an input. To reconcile this contradiction, this paper intends to propose a global, directional distance function model based on previous study to investigate the productivity, economic efficiency, CO₂ emissions efficiency, and marginal abatement cost of the China’s regional transportation sectors during 2007–2012. The results show that: (1) the productivity, economic efficiency and CO₂ emissions efficiency of different regions differ widely. More specifically, the coastal areas of south China perform better than the other areas in terms of productivity, economic efficiency, and CO₂ emissions efficiency. (2) Generally, the economic efficiency is greater than CO₂ emissions efficiency, which is relatively low in most areas. (3) A negative correlation is found between CO₂ emissions efficiency and its marginal abatement cost. For a 1% increase in CO₂ emissions efficiency, the CO₂ marginal abatement cost declines by 102 Yuan (in 2004 constant price). The results imply that improving CO₂ emissions efficiency plays an important role in marginal abatement cost reduction, and it also provides us a new approach to reduce abatement cost besides the technical progress.     

Impacts of an emission based private car taxation policy - First year ex-post analysis

This paper assesses the impacts of a targeted policy designed to influence car purchasing trends towards lower CO₂ emitting vehicles. Vehicle registration tax and annual motor tax rates in Ireland changed in July 2008 from being based on engine size to emissions performance of cars. This paper provides a one year ex-post analysis of the first year of the tax change, tracking the change in purchasing trends arising from the measure related to specific CO₂ emissions, engine size and fuel, and the implications for car prices, CO₂ emissions abatement, and revenue gathered. While engine efficiency improvements had been offset by purchasing trends towards larger and generally less efficient cars in the past, with the average MJ/km remaining constant from 2000 to 2007, this analysis shows that in the first year of the new taxation system the average specific emissions of new cars fell by 13% to 145 g/km. This was brought about, not by a reduction in engine size, but rather through a significant shift to diesel cars. Despite an unexpected reduction in car sales due to a recession in 2008, the policy measure has had a larger than anticipated impact on CO₂ emissions, calculated to be 5.9 ktCO₂ in the first year of the measure. The strong price signal did however result in a 33% reduction in tax revenue from VRT, in financial terms amounting to a drop of €166 million compared to a baseline situation.     

Promoting Public Transport Using Marketing Techniques in Mobility Management and Verifying their Quantitative Effects

Mobility management (MM) is a transportation management policy that uses “soft” measures to attempt to reduce car use and promote sustainable transportation modes such as public transport, bicycles, and walking. Using communication and other means, MM induces voluntarily change towards more sustainable transportation modes. We implemented MM marketing to promote an experimental community bus service. This project had two components: a questionnaire conducted in the service area and a monthly newsletter. The questionnaire was more than a survey; it also communicated information about the bus and helped promote bus use. One month after the survey, we implemented a follow-up survey targeting the initial survey respondents. Results suggest that the MM program produced a general increase in bus use, as well as mouth-to-mouth advertising, that helped promote bus use.     

Economic and ecological optimization of electric bus charging considering variable electricity prices and CO2eq intensities

In many cities, diesel buses are being replaced by electric buses with the aim of reducing local emissions and thus improving air quality. The protection of the environment and the health of the population is the highest priority of our society. For the transport companies that operate these buses, not only ecological issues but also economic issues are of great importance. Due to the high purchase costs of electric buses compared to conventional buses, operators are forced to use electric vehicles in a targeted manner in order to ensure amortization over the service life of the vehicles. A compromise between ecology and economy must be found in order to both protect the environment and ensure economical operation of the buses.In this study, we present a new methodology for optimizing the vehicles’ charging time as a function of the parameters CO_2eq emissions and electricity costs. Based on recorded driving profiles in daily bus operation, the energy demands of conventional and electric buses are calculated for the passenger transportation in the city of Aachen in 2017. Different charging scenarios are defined to analyze the influence of the temporal variability of CO_2eq intensity and electricity price on the environmental impact and economy of the bus. For every individual day of a year, charging periods with the lowest and highest costs and emissions are identified and recommendations for daily bus operation are made. To enable both the ecological and economical operation of the bus, the parameters of electricity price and CO₂ are weighted differently, and several charging periods are proposed, taking into account the priorities previously set. A sensitivity analysis is carried out to evaluate the influence of selected parameters and to derive recommendations for improving the ecological and economic balance of the battery-powered electric vehicle.In all scenarios, the optimization of the charging period results in energy cost savings of a maximum of 13.6% compared to charging at a fixed electricity price. The savings potential of CO_2eq emissions is similar, at 14.9%. From an economic point of view, charging between 2 a.m. and 4 a.m. results in the lowest energy costs on average. The CO_2eq intensity is also low in this period, but midday charging leads to the largest savings in CO_2eq emissions. From a life cycle perspective, the electric bus is not economically competitive with the conventional bus. However, from an ecological point of view, the electric bus saves on average 37.5% CO_2eq emissions over its service life compared to the diesel bus. The reduction potential is maximized if the electric vehicle exclusively consumes electricity from solar and wind power.     

A new statistical method of assigning vehicles to delivery areas for CO2 emissions reduction

Transportation CO₂ emissions are expected to increase in the following decades, and thus, new and better alternatives to reduce emissions are needed. Road transport emissions are explained by different factors, such as the type of vehicle, delivery operation and driving style. Because different cities may have conditions that are characterized by diversity in landforms, congestion, driving styles, etc., the importance of assigning the proper vehicle to serve a particular region within the city provides alternatives to reduce CO₂ emissions. In this article, we propose a new methodology that results in assigning trucks to deliver in areas such that the CO₂ emissions are minimized. Our methodology clusters the delivery areas based on the performance of the vehicle fleet by using the k-means algorithm and Tukey’s method. The output is then used to define the optimal CO₂ truck-area assignment. We illustrate the proposed approach for a parcel company that operates in Mexico City and demonstrate that it is a practical alternative to reduce transportation CO₂ emissions by matching vehicle type with delivery areas.     

An optimization model for bus fleet replacement with budgetary and environmental constraints

ABSTRACT

As maintenance and operation costs increase with usage over time, equipment is replaced when the value of new equipment is more attractive. Some methods have been developed to solve this problem. In the public transport sector, such problems are frequently analyzed by fleet managers and determined by bus age restriction regulations. We propose an Integer Programming model that integrates both budgetary and environmental constraints (CO₂ emissions) which, as far as we know, have not previously been studied in conjunction. The study aims to determine the optimal replacement plan for a fleet of diesel buses of different size, age, maintenance costs and emissions rates, with new (less polluting) diesel buses over a time horizon of 50 years. The results indicate that it is possible to reduce emissions with a low annual budget using an optimal replacement policy.     

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.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

Valorization of carbon dioxide by conversion into fuel using renewable energy in Algeria

Reducing the emissions of the main anthropogenic greenhouse gases, such as carbon dioxide (CO₂), is one of the major challenges of this century. A partial solution to these environmental problems could be the capture and the conversion of carbon dioxide. The main objective of the present work is to study the opportunities and prospects of recycling carbon dioxide to produce synthetic fuel, particularly methanol, which is a complementary technology to carbon capture and storage (CCS). This methanol will be produced by using several renewable energies, such as solar, wind and geothermal, for the purpose of using it in the transportation sector in Algeria. In 2013, Algeria’s total amount of CO₂ emissions (created by energy consumption) was 143 million tonnes. It is estimated that 44.4 million tonnes of CO₂ can be captured from the exhaust of stationary units (factories and power stations) and converted to methanol every year. By adopting this process, approximately 32 million tonnes of methanol can be produced with an energy value of 580,000 TJ. The methanol produced from CO₂ can be used as an alternative transportation fuel. For this reason, the Geographical Information System (GIS) is used to present the spatial distribution of the methanol demand in short and long terms, based on market penetration rates, vehicle fleet and population data. An analysis of the energy balance, environment and economics of CO₂ recycling process is presented. In terms of environmental performance, the reduction in carbon dioxide emissions that come from the transport sector was remarkable in 2045.     

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.