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.     

Effects of battery chemistry and performance on the life cycle greenhouse gas intensity of electric mobility

Lithium traction batteries are a key enabling technology for plug-in electric vehicles (PEVs). Traction battery manufacture contributes to vehicle production emissions, and battery performance can have significant effects on life cycle greenhouse gas (GHG) emissions for PEVs. To assess emissions from PEVs, a life cycle perspective that accounts for vehicle production and operation is needed. However, the contribution of batteries to life cycle emissions hinge on a number of factors that are largely absent from previous analyses, notably the interaction of battery chemistry alternatives and the number of electric vehicle kilometers of travel (e-VKT) delivered by a battery. We compare life cycle GHG emissions from lithium-based traction batteries for vehicles using a probabilistic approach based on 24 hypothetical vehicles modeled on the current US market. We simulate life-cycle emissions for five commercial lithium chemistries. Examining these chemistries leads to estimates of emissions from battery production of 194–494 kg CO₂ equivalent (CO₂e) per kWh of battery capacity. Combined battery production and fuel cycle emissions intensity for plug-in hybrid electric vehicles is 226–386 g CO₂e/e-VKT, and for all-electric vehicles 148–254 g CO₂e/e-VKT. This compares to emissions for vehicle operation alone of 140–244 g CO₂e/e-VKT for grid-charged electric vehicles. Emissions estimates are highly dependent on the emissions intensity of the operating grid, but other upstream factors including material production emissions, and operating conditions including battery cycle life and climate, also affect life cycle GHG performance. Overall, we find battery production is 5–15% of vehicle operation GHG emissions on an e-VKT basis.     

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.     

The potential mitigation of CO2 emissions via modal substitution of high-speed rail for short-haul air travel from a life cycle perspective – An Australian case study

The objective of this study is to provide a strategic evaluation of the mitigation of CO₂ emissions via modal substitution of high-speed rail for short-haul air travel on the Sydney–Melbourne, Australia city-pair from a life cycle perspective. It has been demonstrated that when considering CO₂ emissions from vehicle operations, the modal shift from air to high-speed rail on this city-pair has the potential to provide a means of CO₂ mitigation. However, uncertainty exists with regard to the level of mitigation potential when considering the whole-of-life performance of the systems. Given the significant difference in the infrastructure requirements between the air mode and the high-speed rail mode, this study quantifies the life cycle CO₂ load attributable to each system and examines the effect on CO₂ mitigation potential. The study concluded that while the inclusion of the linehaul infrastructure did increase the CO₂ load associated with high-speed rail mode, it did not equate to or exceed the CO₂ load per trip as experienced by the air mode. The avoided annual life cycle CO₂ emission in the target year 2056 was 0.37 Mt representing an 18% reduction when compared to the air mode only on the city pair. In fact, the scenario comparison indicated that the substitution of high-speed rail for short-haul air travel on the city pair resulted in CO₂ emissions avoidance throughout the longitudinal period.     

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.     

Vehicle restrictions and CO2 emissions in Beijing – A simple projection using available data

The Beijing Government launched a new policy on restricting vehicle ownership in late 2010 to regulate the faster motorization and the excessive vehicular carbon dioxide (CO₂) emissions. In this paper, we first analyzed this policy and its effect on private passenger vehicle population. The private passenger vehicle population in Beijing from 2011 to 2020 was predicted under three different scenarios: no constraint (NC), current constraint (CC) and tighter constraint (TC). Then the assessment of vehicular emissions reduction benefits was made on the basis of private passenger vehicle population, vehicle kilometers traveled and CO₂ emission factors. It was projected that the CO₂ emissions in 2020 will reach 23.90, 15.55 and 13.23 million tons under NC, CC and TC respectively. The policy is very effective in controlling the faster motorization and reducing CO₂ emissions.     

Approaches and Techniques for Modelling CO2 Emissions from Road Transport

Abstract

Transport accounts for around a quarter of CO₂ emissions globally. Transport modelling provides a useful means to explore the dynamics, scale and magnitude of transport-related emissions. This paper explores the modelling tools available for analysing the emissions of CO₂ from transport. Covering a range of techniques from transport microsimulation to global techno-economic models, this review provides insights into the various advantages and shortcomings of these tools. The paper also examines the value of having a broad range of perspectives for analysing emissions from transport. The paper concludes by suggesting that the broad range of models creates a rich environment for exploring a spectrum of policy questions around the emissions from transport, and the potential for combining modelling approaches further enhances the understanding that can be attained.     

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.     

A system dynamics model of CO2 mitigation in China’s inter-city passenger transport

Mitigation of greenhouse gas emissions from transportation has become increasingly important and challenging especially for developing countries. This paper takes the inter-city passenger transport in China as a case, and develops a system dynamics model for policy assessment and CO₂ mitigation potential analysis. It is found that the future demand for China’s inter-city passenger transport is expected to be large, with the turnover volume growing at a rate of 9% per annum and amounting to 6600 billion p-km in 2020. Major emissions reduction potential exists in inter-city passenger transport. In 2020, comparing to the case without any specific policies stressing mitigation, the reduction of CO₂ emissions ranges from 26% to 32% under those scenarios with policy controls. Sensitivity analysis reveals that the CO₂ mitigation will be best achieved by accelerating the development of railway network, together with slowing down the extension of highway network and imposing fuel taxes.     

A valuation of the environmental performance of vehicles: an analysis and comparison of two methodologies

The European Clean Vehicle Directive was introduced in 2009 to create an obligation on public authorities to take into account the impact of energy consumption, carbon dioxide (CO₂) emissions and pollutant emissions into their purchasing decisions for road transport vehicles. This should stimulate the market for clean and energy-efficient vehicles and improve transport's impact on environment, climate change and energy use. Therefore the so-called ‘Operational Lifetime Cost’ of a vehicle is calculated, divided into the cost for energy consumption, CO₂ and pollutant (nitrous oxide, particulate matter, non-methane hydrocarbons) emissions. In Belgium, a different methodology has been developed to calculate the environmental impact of a vehicle, called ‘Ecoscore’, based on a well-to-wheel approach. More pollutants are included compared to the Clean Vehicle methodology, but also indirect emissions are taken into account. In this paper, both methodologies are compared and used to analyze the environmental performance of passenger cars with different fuel types and from different vehicle segments. Similar rankings between both methodologies are obtained; however, the large impact of energy use (and CO₂ emissions) in the Clean Vehicle methodology disadvantages compressed natural gas cars, as well as diesel cars equipped with particulate filters, compared to the Ecoscore methodology.     

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.     

Light duty gasoline vehicle emission factors at high transient and constant speeds for short road segments

Vehicle emissions estimates are needed at high spatial and temporal resolution to estimate near-roadway air quality and human exposures. The MOBILE6 emission factor model is based on transient test cycles of less than 65 mph. Correction factors for high speed and constant speed are developed based on vehicle-specific power-based modal models for light duty gasoline vehicles, using data from portable emission measurement systems. At 80 mph versus 65 mph, the estimated average emission rates are greater by 30%, 20%, 80%, and 10% for NO_x, HC, CO, and CO₂. The ratio of constant to average of transient speed emission rates range from 0.49 to 0.94 for NO_x at speeds of 20 mph and 80 mph. The high speed and constant speed correction factors are applied to estimate vehicle emissions for a freeway segment that includes vehicle cruising speeds between 65 and 80 mph. The potential error for not accounting for constant speed operation on a short segment of highway could be 49% at moderate speed and 24% at high speed.     

Exhaust emissions and fuel consumption of a triple-fuel spark-ignition engine powered passenger car

This paper examines the influence of compressed natural gas, liquefied petroleum gas and gasoline fuel on the exhaust emissions and the fuel consumption of a spark-ignition engine powered passenger car. The vehicle was driven according to the urban driving cycle and extra urban driving cycle speed profiles with the warmed-up engine. Cause and effect based analysis reveals potential for using different fuels to reduce vehicle emission and deficiencies associated with particular fuels. The highest tank to wheel efficiency and the lowest CO₂ emission are observed with the natural gas fuelled vehicle, that also featured the highest total hydrocarbon emissions and high NO_x emissions because of fast three way catalytic converter aging due the use of the compressed natural gas. Retrofitted liquefied petroleum gas fuel supply systems feature the greatest air-fuel ratio variations that result in the lowest TtW efficiency and in the highest NO_x emissions of the liquefied gas fuelled vehicle.     

Improvement in the estimation and back-extrapolation of CO2 emissions from the Irish road transport sector using a bottom-up data modelling approach

Road transport is a major source of CO₂ emissions in Ireland and accounts for almost 96% of the total CO₂ emissions from the transport sector. Following the recent adopted UNFCCC reporting guidelines on annual inventories [24/CP.19], this study applied the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2006 IPCC GLs) tier 3 approach to estimate CO₂ emissions from road transport at the vehicle category level, for the first time in Ireland. For this, disaggregated datasets were prepared based on year of vehicle registration and mileage since registration of the vehicle. Such an approach provided a more realistic national scenario in comparison to the use of average mileage degradation in emission calculations. This investigation comprised a recalculation of previous emissions estimates (1990–2012) and an estimation of CO₂ emissions in 2013 using a previously unavailable level of data disaggregation for vehicle mileage as well as using vehicle class specific data and an improved bottom-up estimation methodology in COPERT. Historic vehicle fleet data were restructured, annual mileage data were estimated in relation to the fleet data and back extrapolated using a regression approach.The results showed that the mileage degradation was not only subject to fuel technology, engine size, and age but also the emissions class and vehicle category. It was also observed that the disaggregated level of data provided a different CO₂ emissions split among the vehicle categories than that of previous estimations which were based on an aggregated level of data. Previous emissions inventories (1990–2012) were shown to have underestimated the share from diesel fuelled passenger cars by more than 56% in 2012. Diesel fuelled passenger cars were also found to account for the majority of CO₂ emissions from road transport activities in Ireland in 2013. The level and trend assessment showed that emissions from Euro-II and Euro-III classed vehicles especially for passenger cars, which have a significant contribution to the total emission in 2013 have caused an increase in fleet level emissions in Ireland. In addition, the results also showed that the emissions share from Light Duty Vehicles and Heavy Duty Vehicles were overestimated by previous investigations. This paper highlights the importance of the resolution of data used in emissions inventory preparation which may impact upon future projections and policy formulation. The findings of this investigation are also discussed in relation their implications for road transport policy, including carbon taxation and future policy options aimed at achieving EU emissions target in 2020.     

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.     

CO2 emissions correction of light-duty vehicles based on an energy deviation analysis method

In present study, a total of 3 types of light-duty vehicles were tested for 7 types of driving modes by using a vehicle dynamics-based simulation method. Deviations between the target and actual test vehicle speed and inaccurate chassis dynamometer road load settings are selected as the two main factors affecting the CO₂ emission measurement test. 126 cases of simulations were conducted to analyze the effects of the deviation between the target and actual test vehicle speed on CO₂ emissions and 63 cases of simulation were conducted to analyze the effectiveness of inaccurate road load test conditions on CO₂ emissions. Then, the CO₂ correlation method proposed by World Forum for Harmonization of Vehicle Regulations (WP.29, UN) was applied for simulated results in original simulation cases, and a correction to performance was validated by comparative analysis. From the simulation results, it is revealed that velocity and road load deviation are related to distinct changes in fuel efficiency and CO₂ emission rates of test vehicles. Also, it is revealed that CO₂ correction method show good performance to reduce the relative error lower than 2% in all test cases.     

The diffusion of cleaner vehicles in CO2 emission trading designs

The accelerated diffusion of cleaner vehicles to reduce CO₂ emissions in transport can be explicitly integrated in emission trading designs by making use of cross-sectoral energy efficiency investment opportunities that are found in data on CO₂ emissions during the production and the use of cars and trucks. We therefore elaborate the introduction of tradable certificates that are allocated or grandfathered to manufacturers that provide vehicles (and other durable goods) that enable their customers to reduce their own CO₂ emissions. This certificate is an allowance for each tonne CO₂ avoided. Manufacturers can then sell these certificates on the emission market and use the revenues to lower the price of their cleanest vehicles. This mechanism should partially overcome the price difference with less efficient cars. In a simulation, we found that the introduction of the certificate in tradable permit systems can lead to very significant reductions of CO₂ emissions. The simulations indicate that CO₂ emissions resulting from the car fleet can be reduced by 25 to 38% over a period of 15 years (starting in 1999). For the truck fleet, the reduction potential is more limited but still very interesting.     

VISSIM/MOVES integration to investigate the effect of major key parameters on CO2 emissions

This paper looks at CO₂ emissions on limited access highways in a microscopic and stochastic environment using an optimal design approach. Estimating vehicle emissions based on second-by-second vehicle operation allows the integration of a microscopic traffic simulation model with the latest US Environmental Protection Agency’s mobile source emissions model to improve accuracy. A factorial experiment on a test bed prototype of the I-4 urban limited access highway corridor located in Orlando, Florida was conducted to identify the optimal settings for CO₂ emissions reduction and to develop a microscopic transportation emission prediction model. An exponentially decaying function towards a limiting value expressed in the freeway capacity is found to correlate with CO₂ emission rates. Moreover, speeds between 55 and 60 mph show emission rate reduction effect while maintaining up to 90% of the freeway’s capacity. The results show that speed has a significant impact on CO₂ emissions when detailed and microscopic analysis of vehicle operations of acceleration and deceleration are considered.     

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.     

Economic valuation of Well-To-Wheel CO2 emissions from freight transport along the main transalpine corridors

CO₂ emissions are one of the main externalities related to freight transport. Their evaluation is extremely difficult, due to the presence of several scientific and economic uncertainties. This paper discusses the approaches currently adopted by literature to deal with CO₂, proposing a methodology based on a Well-To-Wheel quantification and an economic valuation deriving from a meta-regression. A freight transport analysis is then provided for one of the most critical areas of Europe, the Alps. Here, the different approaches adopted by the single nations determine divergent results in terms of modal shift towards rail and, consequently, CO₂ emissions. An integrated and transnational strategy could lead to better results, avoiding detoured traffic and increasing the share of railway traffic. To this aim, the carbon impacts of three specific alpine-wide measures are evaluated: namely, Alpine Crossing Exchange, Emissions Trading and Differentiated Toll System. In comparison with business-as-usual scenario, the case study reveals a potential CO₂ saving up to more than 600,000 tons and 38 M€ for the year 2030, thus providing policy makers with an integrative transnational tool able to evaluate the long-term carbon impact of their transport decisions.