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.     

Effects of the polycentric spatial structures of Chinese city regions on CO2 concentrations

The environmental sustainability of polycentric spatial structures in urban planning must be evaluated to ensure the sustainable development of city regions. Given the mixed conclusions of previous studies, as well as the lack of information on reliable methods of assessment and quantifiable mechanisms, a three-year dataset for prefecture-level and above city regions in China and spatial econometric models were used to examine the relationship between regional polycentricity and CO₂ concentrations. After robust testing, we confirmed that polycentric structures decrease the mean CO₂ concentrations of city regions, significantly reducing CO₂ concentrations in primary city centers and mildly increasing those in city subcenters. Further quantitative analyses of the mechanisms underlying these patterns revealed that the CO₂-reduction effect of polycentric structures is due to the balancing of reductions in commuting duration, transference of industrial CO₂ to neighboring areas, and an increase in household CO₂ emissions.     

Combining technology development and behaviour change to meet CO2 cumulative emission budgets for road transport: Case studies for the USA and Europe

Global temperature rise over the long term will be proportional to the total amount of CO₂ emitted. Any given probability of exceeding a targeted maximum temperature rise implies a maximum limit on the cumulative total of CO₂ that can be emitted: a CO₂ “budget”. This paper describes an approach to modelling cumulative emissions from light and heavy duty road transport from the present to 2050, focussing on the USA and Europe, and comparing the potential impacts of a range of technological and behaviourally-based abatement measures with such cumulative emissions budgets.The model shows that abatement measures would have a lower effect on cumulative emissions from 2000 to 2050 than on annual emissions in 2050, so that focussing only on annual emissions could be misleading. It shows that technological developments would be insufficient on their own to enable Europe and the USA to meet CO₂ budgets for road transport. Behavioural changes, which potentially can be implemented much sooner, would be essential too. There is potential to keep European light duty emissions very close to CO₂ budgets, and US light duty emissions not far above the least restrictive budget, but the model predicts that heavy duty emissions in both regions are likely to exceed their CO₂ budgets. Deeper emissions reductions in other regions and sectors will be needed to compensate for this. Timing would be critical: for the greatest impact, behaviour change policies and interventions would need to be applied early and deeply.     

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.     

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.     

The future tourism mobility of the world population: Emission growth versus climate policy

Much of global passenger transport is linked to tourism. The sector is therefore of interest in studying global mobility trends and transport-related emissions. In 2005, tourism was responsible for around 5% of all CO₂ emissions, of which 75% were caused by passenger transport. Given the rapid growth in tourism, with 1.6 billion international tourist arrivals predicted by 2020 (up from 903 million in 2007), it is clear that the sector will contribute to rapidly growing emission levels, and increasingly interfere with global climate policy. This is especially true under climate stabilisation and “avoiding dangerous climate change” objectives, implying global emission reductions in the order of −50% to −80% by 2050, compared to 2000. Based on three backcasting scenarios, and using techniques integrating quantitative and qualitative elements, this paper discusses the options for emission reductions in the tourism sector and the consequences of mitigation for global tourism-related mobility by 2050. It ends with a discussion of the policy implications of the results.     

Co-benefits of low carbon passenger transport actions in Indian cities: Case study of Ahmedabad

Rising population, income and urbanization are increasing urban passenger transport demand in India. Energy and emissions intensities associated with conventional transport are no longer sustainable vis-a-vis energy security, air quality and climate change. Cities are seeking transport roadmaps that jointly mitigate these risks. Roadmaps vary across cities, but approach to delineate actions is common: (i) ‘representative vision’ that articulates long-term goals, (ii) methods for comparative scenarios assessment, and (iii) quantification of co-benefits to prioritize actions. This paper illustrates application of quantitative modeling to assess development and environmental co-benefits for Ahmedabad city. The paper constructs two transport scenarios spanning till 2035. The bifurcating themes are: (i) Business-as-Usual (BAU) and Low Carbon Scenario (LCS). The quantitative assessment using Extended Snapshot (ExSS) Model shows that transport activity shall result in four-fold increase in energy demand under BAU from 2010 to 2035. Three key contributors to CO₂ mitigation under LCS in merit order are: (i) fuel switch, including decarbonized electricity, (ii) modal shift, and (iii) substitution of travel demand. Scenarios analysis shows that LCS improves energy security by reducing oil demand and also delivers air quality co-benefits – reducing 74% NOx and 83% PM_2.5 from the passenger transport sector compared to BAU in 2035. Finally, the paper argues that cities in developing countries can leverage carbon finance to develop sustainable and low carbon mobility plans that prevent adverse infrastructure and behavioral lock-ins and prompt low carbon development.     

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.     

Simulating deep CO2 emission reduction in transport in a general equilibrium framework: The GEM-E3T model

Transport sector restructuring to achieve deep GHG emission cuts has attracted much attention because transportation is important for the economy and inflexible in greenhouse gas emission reduction. The aim of this paper is to simulate transition towards low carbon transportation in the European Union until 2050 and to assess the ensuing macroeconomic and sectorial impacts. Transport restructuring is dynamically simulated using a new transport-oriented version of the computable general equilibrium model GEM-E3 which is linked with the PRIMES-TREMOVE energy and transport sectors model. The analysis draws from comparing a reference scenario projection for the EU member-states up to 2050 to alternative transport policy scenarios and sensitivities which involve deep cutting of CO₂ emissions. The simulations show that transport restructuring affects the economy through multiple channels, including investment in infrastructure, the purchasing and manufacturing of new technology vehicles, the production of alternative fuels, such as biofuels and electricity. The analysis identifies positive impacts of industrial activity and other sectors stemming from these activities. However, the implied costs of freight and passenger transportation are of crucial importance for the net impact on GDP and income. Should the transport sector transformation imply high unit costs of transport services, crowding out effects in the economy can offset the benefits. This implies that the technology and productivity progress assumptions can be decisive for the sign of GDP impacts. A robust conclusion is that the transport sector decarbonisation, is likely to have only small negative impacts on the EU GDP compared to business as usual.     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

Energy use reduction potential of passenger transport in Europe

To contribute to a sustainable society, considerable reduction in energy use and CO₂ emissions should be achieved. This paper presents the results of calculations exploring the energy use reduction potential of passenger transport for Western Europe (OECD Europe minus Turkey). For these calculations, three types of options are defined emphasizing technological, infrastructural and behavioural change. By 2050, technological improvements may reduce energy use per passenger-km by - 30%. Adding infrastructural options, an energy reduction of > 50% by 2050 can be realised. To achieve further energy reductions, options with a large behavioural impact should also be implemented. This results in an 80% energy reduction potential in the transport sector by 2050. To calculate the reduction potential on OECD Europe level, one should factor in expectations concerning mobility growth. Two mobility development scenarios are used. Both scenarios foresee a net decrease in total energy use of 20% with the introduction of the technological and infrastructural improvement options. Adding options emphasizing behavioural change results in a net reduction potential of - 60% by 2050.     

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.     

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.     

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.     

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.     

Freight Transport Deceleration: Its Possible Contribution to the Decarbonisation of Logistics

The paper challenges the conventional view that the movement of goods through supply chains must continue to accelerate. The compression of freight transit times has been one of the most enduring logistics trends but may not be compatible with governmental climate change policies to cut greenhouse gas emissions by 60–80% by 2050. Opportunities for cutting CO₂ emissions by ‘despeeding' are explored within a freight decarbonisation framework and split into three categories: direct, indirect and consequential. Discussion of the direct carbon savings focuses on the trucking and deep-sea container sectors, where there is clear evidence that slower operation cuts cost, energy and emissions and can be accommodated within current supply chain requirements. Indirect emission reductions could accrue from more localised sourcing and a relaxation of just-in-time (JIT) replenishment. Acceleration of logistical activities other than transport could offset increases in freight transit times, allowing the overall carbon intensity of supply chains to reduce with minimal loss of performance. Consequential deceleration results from other decarbonisation initiatives such as freight modal split and a shift to lower carbon fuels. Having reviewed evidence drawn from a broad range of sources, the paper concludes that freight deceleration is a promising decarbonisation option, but raises a number of important issues that will require new empirical research.     

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.     

The influence of integrated space–transport development strategies on air pollution in urban areas

The phenomenon of urban sprawl has strong impacts on transport performance and accessibility and causes an increase of air pollution. Effective control of urban sprawl requires an integrated approach comprising urban transport and land-use planning. Current research is insufficient to demonstrate the effects of urban sprawl on travel behavior and air pollution emission. The present paper examines the potential of an integrated approach on space–transport development strategies with the aim of increasing accessibility and reducing air pollution. A combination of space and transport strategies has been simulated for the rapidly expanding city of Surabaya. A comparative analysis of the impact of those cases indicates the promising potential alternatives to minimize the phenomenon. The transport options considered are combinations of Public Transport (PT), comprising Mass Rapid Transit (MRT), Light Rapid Transit (LRT), and Bus Rapid Transit (BRT). The options for urban structure include a compact zone development for the city, as formulated by the city planning agency, and a polycentric city set-up based on a job-housing balance aimed at minimizing the house-job distance. The results indicate that the polycentric city structure has the potential to make public transport work successfully for the city of Surabaya. This city structure creates a trip demand pattern which matches citizens’ PT preferences. Compared to the current situation, the combination of such a city structure with an expansion of PT systems would lead to a considerable improvement of transport performance, i.e. a PT mode share, a mean commute distance, and a significant reduction in emissions.     

Understanding job-housing relationship and commuting pattern in Chinese cities: Past,present and future

There are debates about whether job-housing balance and short commuting distances could be achieved through government intervention in Western countries. However, few studies have been carried out in developing context. The present study aims to fill in this knowledge vacuum by studying how China’s changing socio-spatial context, particularly the spatial ideas of danwei, influences job-housing relationships and commuting patterns from a historical perspective. The results clearly show that the dominant trend in commuting patterns in Chinese cities has changed from intra-danwei commuting before 1978 to reverse commuting from the city center to the inner suburbs in 1978–1998, to long-distance suburb-to-city commuting since 1998. The findings suggest that government intervention could be helpful in achieving shorter commute in China, and that urban planning and policy that promote mixed land-use and job-housing balance should be considered. Some limitations of government intervention are also discussed.