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.     

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.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

Biofuel futures in road transport – A modeling analysis for Sweden

First and second generation biofuels are among few low-carbon alternatives for road transport that currently are commercially available or in an early commercialization phase. They are thus potential options for meeting climate targets in the medium term. For the case of Sweden, we investigate cost-efficient use of biofuels in road transport under system-wide CO₂ reduction targets to 2050, and the effects of implementation of targets for an almost fossil-free road transport sector to 2030. We apply the bottom-up, optimization MARKAL_Sweden model, which covers the entire Swedish energy system including the transport sector. For CO₂ reductions of 80% to 2050 in the Swedish energy system as a whole, the results of the main scenario show an annual growth rate for road transport biofuels of about 6% from 2010 to 2050, with biofuels accounting for 78% of road transport final energy use in 2050. The preferred biofuel choices are methanol and biomethane. When introducing additional fossil fuel phase-out policies in road transport (−80% to 2030), a doubling of the growth rate to 2030 is required and system CO₂ abatement costs increases by 6% for the main scenario. Results imply that second generation biofuels, along with energy-efficient vehicle technologies such as plug-in hybrids, can be an important part of optimized system solutions meeting stringent medium-term climate targets.     

Application of the support vector machine and heuristic k-shortest path algorithm to determine the most eco-friendly path with a travel time constraint

This study aims to determine an eco-friendly path that results in minimum CO₂ emissions while satisfying a specified budget for travel time. First, an aggregated CO₂ emission model for light-duty cars is developed in a link-based level using a support vector machine. Second, a heuristic k-shortest path algorithm is proposed to solve the constrained shortest path problem. Finally, the CO₂ emission model and the proposed eco-routing model are validated in a real-world network. Specifically, the benefit of the trade-off between CO₂ emission reduction and the travel time budget is discussed by carrying out sensitivity analysis on a network-wide scale. A greater spare time budget may enable the eco-routing to search for the most eco-friendly path with higher probability. Compared to the original routes selected by travelers, the eco-friendly routes can save an average of 11% of CO₂ emissions for the trip OD pairs with a straight distance between 6 km and 9 km when the travel time budget is set to 10% above the least travel time. The CO₂ emission can also be reduced to some degree for other OD pairs by using eco-routing. Furthermore, the impact of market penetration of eco-routing users is quantified on the potential benefit for the environment and travel-time saving.     

The effectiveness and costs of speed reductions on emissions from international shipping

Greenhouse gas emissions from international shipping are an increasing concern. The paper evaluates whether vessel speed reduction can be a potentially cost-effective CO₂ mitigation option for ships calling on US ports. By applying a profit-maximizing equation to estimate route-specific, economically-efficient speeds, we explore policy impacts of a fuel tax and a speed reduction mandate on CO₂ emissions. The profit-maximizing function incorporates opportunity costs associated with speed reduction that go unobserved in more traditional marginal abatement cost analyses. We find that a fuel tax of about $150/ton fuel will lead to average speed-related CO₂ reductions of about 20–30%. Moreover, a speed reduction mandate targeted to achieve 20% CO₂ reduction in the container fleet costs between $30 and $200 per ton CO₂ abated, depending on how the fleet responds to a speed reduction mandate.     

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.     

Comparing the impact of future airline network change on emissions in India and the United States

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.     

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%.     

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.     

Development of the World-wide harmonized Light duty Test Cycle (WLTC) and a possible pathway for its introduction in the European legislation

This paper presents the World-wide harmonized Light duty Test Cycle (WLTC), developed under the Working Party on Pollution and Energy (GRPE) and sponsored by the European Union (with Switzerland) and Japan. India, Korea and USA have also actively contributed. The objective was to design the harmonized driving cycle from “real world” driving data in different regions around the world, combined with suitable weighting factors. To this aim, driving data and traffic statistics of light duty vehicles use were collected and analyzed as basic elements to develop the harmonized cycle. The regional driving data and weighting factors were then combined in order to develop a unified database representing the worldwide light duty vehicle driving behavior. From the unified database, short trips were selected and combined to develop a driving cycle as representative as possible of the unified database. Approximately 765,000 km of data were collected, covering a wide range of vehicle categories, road types and driving conditions. The resulting WLTC is an ensemble of three driving cycles adapted to three vehicle categories with different power-to-mass ratio (PMR). It has been designed as a harmonized cycle for the certification of light duty vehicles around the world and, together with the new harmonized test procedures (WLTP), will serve to check the compliance of vehicle pollutant emissions with respect to the applicable emissions limits and to establish the reference vehicle fuel consumption and CO₂ performance.     

Estimating transboundary economic damages from climate change and air pollution for subnational incentives for green on-road freight

Subnational incentives to adopt zero emission vehicles (ZEVs) are critical for reducing the external economic damages posed by transportation to air quality and the climate. Few studies estimate these damages for on-road freight, especially at scales relevant for subnational policies requiring cross-border cooperation. Here, we assess the damages to US receptors from emissions of air pollutants (PM_2.5, NO_x, SO₂, NH₃), and greenhouse gases (CO₂, CH₄, N₂O) from medium and heavy duty freight trucking, and the benefits of ZEV adoption by census division in the Province of Ontario. We develop an integrated modelling framework connecting a travel demand model, a mobile emissions simulator, and a regression based marginal damages model of air pollutants and climate change. We estimate $1.9 billion (2010 USD) in annual cross-border damages, or $0.16/VKT, resulting from scaled up atmospheric emissions from a ‘typical day’ of medium and heavy duty truck traffic volume for Ontario in 2012. This implies approximately $8000 per truck per year in damages, which could inform an economic incentive for emission reduction. The provincial goal of 5% ZEV adoption would reduce GHG emissions in 2012 by 800 ktCO₂e, yielding $89 Million (2010 USD) in cross-border benefits annually, with air quality co-benefits of $83/tCO₂e. This result varies between −19% and 22% based on sensitivity analysis for travel and emissions models, though economic damages are likely the largest uncertainty source. Such advances in subnational scale integrated modeling of the environmental impacts of freight can offer insights into the sustainable design of clean freight policy and programs.     

Electric and hydrogen buses: Shifting from conventionally fuelled cars in the UK

For the UK to meet their national target of net zero emissions as part of the central Paris Agreement target, further emphasis needs to be placed on decarbonizing public transport and moving away from personal transport (conventionally fuelled vehicles (CFVs) and electric vehicles (EVs)). Electric buses (EBs) and hydrogen buses (HBs) have the potential to fulfil requirements if powered from low carbon renewable energy sources.A comparison of carbon dioxide (CO₂) emissions produced from conventionally fuelled buses (CFB), EBs and HBs between 2017 and 2050 under four National Grid electricity scenarios was conducted. In addition, emissions per person at different vehicle capacity levels (100%, 75%, 50% and 25%) were projected for CFBs, HBs, EBs and personal transport assuming a maximum of 80 passengers per bus and four per personal vehicle.Results indicated that CFVs produced 30 gCO₂ km⁻¹ per person compared to 16.3 gCO₂ km⁻¹ per person by CFBs by 2050. At 100% capacity, under the two-degree scenario, CFB emissions were 36 times higher than EBs, 9 times higher than HBs and 12 times higher than EVs in 2050. Cumulative emissions under all electricity scenarios remained lower for EBs and HBs.Policy makers need to focus on encouraging a modal shift from personal transport towards sustainable public transport, primarily EBs as the lowest level emitting vehicle type. Simple electrification of personal vehicles will not meet the required targets. Simultaneously, CFBs need to be replaced with EBs and HBs if the UK is going to meet emission targets.     

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.     

Hybrid- and battery-electric vehicles offer low-cost climate benefits in China

Car ownership in China is expected to grow dramatically in the coming decades. If growing personal vehicle demand is met with conventional cars, the increase in greenhouse gas emissions will be substantial. One way to mitigate carbon dioxide (CO₂) emissions from passenger travel is to meet growing demand for cars with alternative vehicles such as hybrid- and battery-electric vehicles (HEVs and BEVs). Our study examines the cost-effectiveness of transitioning from conventional cars to HEVs and BEVs, by calculating their marginal abatement cost (MAC) of carbon in the long-run. We find that transitioning from conventional to hybrid and battery electric light-duty, four-wheel vehicles can achieve carbon emissions reductions at a negative cost (i.e. at a net benefit) in China. In 2030, the average MAC is estimated to be about −$140/ton CO₂ for HEVs and −$515/ton CO₂-saved for BEVs, varying by key parameters. The total mitigation potential of each vehicle technology is estimated to be 1.38 million tons for HEVs and 0.75 million tons for BEVs.     

The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050

The future of US transport energy requirements and emissions is uncertain. Transport policy research has explored a number of scenarios to better understand the future characteristics of US light-duty vehicles. Deterministic scenario analysis is, however, unable to identify the impact of uncertainty on the future US vehicle fleet emissions and energy use. Variables determining the future fleet emissions and fuel use are inherently uncertain and thus the shortfall in understanding the impact of uncertainty on the future of US transport needs to be addressed. This paper uses a stochastic technology and fleet assessment model to quantify the uncertainties in US vehicle fleet emissions and fuel use for a realistic yet ambitious pathway which results in about a 50% reduction in fleet GHG emissions in 2050. The results show the probability distribution of fleet emissions, fuel use, and energy consumption over time out to 2050. The expected value for the fleet fuel consumption is about 450 and 350 billion litres of gasoline equivalent with standard deviations of 40 and 80 in 2030 and 2050, respectively. The expected value for the fleet GHG emissions is about 1360 and 850 Mt CO₂ equivalent with standard deviation of 130 and 230 in 2030 and 2050 respectively. The parameters that are major contributors to variations in emissions and fuel consumption are also identified and ranked through the uncertainty analysis. It is further shown that these major contributors change over time, and include parameters such as: vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel economy of the dominant naturally-aspirated spark ignition vehicles, and percentage of gasoline displaced by cellulosic ethanol. The findings in this paper demonstrate the importance of taking uncertainties into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.     

Real-world gaseous emission characteristics of Euro 6b light-duty gasoline- and diesel-fueled vehicles

To accurately investigate vehicle emissions that have become major contributors to global air pollutants and greenhouse gases, test conditions have been transferred from laboratory type approval test cycles to real-world driving conditions. In this study, the real-world driving emissions of carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NO_x), and carbon dioxide (CO₂) from one gasoline and two diesel Euro 6b light-duty passenger vehicles were investigated by a portable emission measurement system (PEMS) in Lyon, France. NO_x and CO₂ emission controls remain critical to addressing the real-world driving emissions of Euro 6b vehicles. Notably, the tested gasoline vehicle emitted higher CO₂ emissions than diesel vehicles on all types of roads, especially on the urban road with an excess of 29.3–48.3%. The highest emission factors of gaseous pollutants generally occurred on the motorway for the gasoline vehicle, while on the urban road for diesel vehicles. In particular, for high-speed driving conditions, the gasoline vehicle gaseous emissions, especially NO_x emissions, were more affected by acceleration than diesel vehicle emissions. In addition, the CO emissions, especially THC emissions, for the gasoline vehicle, were more influenced by warm-start, especially cold-start, than those for diesel vehicles.     

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.     

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.     

High-speed rail's potential for the reduction of carbon dioxide emissions from short haul aviation: a longitudinal study of modal substitution from an energy generation and renewable energy perspective

Abstract

This paper quantifies and evaluates, utilising a ‘bottom-up’ approach, the effect on CO₂ emissions of a modal shift from short-haul air travel to high-speed rail (HSR), based on projected passenger movements, between Sydney and Melbourne, Australia during the period 2010–2030. To date, peer-reviewed studies assessing the CO₂ emissions from these competing modes of high-speed transportation have been restricted principally to a cross-sectional assessment, with a Eurocentric bias. This present comparative study seeks to address a gap in the literature by assessing, longitudinally, the CO₂ emissions associated with the proposed operation of HSR against the ‘business-as-usual’ air scenario between Sydney and Melbourne. Under the assumed 50/50 modal shift, and the Australian government's current renewable electricity target, an annual reduction in CO₂ emissions of approximately 14% could be achieved when compared with a ‘business-as-usual’ air scenario. This percentage reduction represents a 62 kt reduction in base year, 2010, and a 114 kt reduction in the final year, 2030. In total, the overall reduction achieved by such a modal shift, under the assumed conditions, during the period 2010–2030, equates to approximately 1.87 Mt of CO₂. Importantly, if the electrical energy supply for HSR operations was further ‘decarbonised’, then it follows that a greater emission reduction would be achieved.