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.     

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.     

CO2 emissions in relation to street-network configuration and city size

The street-network efficiency of tens of British cities in relation to transport fuel consumption and CO₂ emissions are analyzed. The results show a strong linear positive correlation between length entropy and average street length, and a negative correlation between entropy and street density. Also, the results suggest that in a large city the street network is used more efficiently than in a small city, as indicated by the sublinear relations between city size (population) and the number of streets, total length of streets, and the area covered by the street network. The sublinear relation means that these parameters grow more slowly than the city size. By contrast, because a larger fraction of the street network is used at close to full capacity during considerable part of the time in a large city than a small one, the fuel consumption and the CO₂ emissions show a linear relation with city size and superlinear relation with total street length. The superlinear relation means that the CO₂ emissions increase faster than the total street length, a measure of the network size. Thus, large cities may be less energy efficient and environmentally friendly than small cities. In every city the street network needs to interconnect all the buildings, which requires a certain minimum size. In a small city, however, the network is used to a low capacity most of the time so that its relations to fuel consumption and the CO₂ emissions are more favorable than those in a large city.     

Impacts of freeway accidents on CO2 emissions: A case study for Orange County,California, US

Traffic congestion caused by traffic accidents contributes to CO₂ emissions. Generally, more efficient and prompt responses to accidents lead to reduced traffic congestion as well as CO₂ emissions. Here we assess the CO₂ emissions impacts of freeway accidents, applies an existing model to capture spatio-temporally congested regions caused by freeway accidents. A case study for the assessment of CO₂ emissions impacts of based on the results from the model is presented.     

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%.     

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.     

Commuters’ exposure to PM2.5 and CO2 in metro carriages of Shanghai metro system

Air quality inside transportation carriages has become a public concern. A comprehensive measurement campaign was conducted to examine the commuters’ exposure to PM_2.5 (d_p ⩽ 2.5 μm) and CO₂ in Shanghai metro system under different conditions. The PM_2.5 and CO₂ concentrations inside all the measured metro lines were observed at 84 ± 42 μg/m³ and 1253.1 ± 449.1 ppm, respectively. The factors that determine the in-carriage PM_2.5 and CO₂ concentrations were quantitatively investigated. The metro in-carriage PM_2.5 concentrations were significantly affected by the ventilation systems, out-carriage PM_2.5 concentrations and the passenger numbers. The largest in-carriage PM_2.5 and CO₂ concentrations were observed at 132 μg/m³ and 1855.0 ppm inside the carriages equipped with the oldest ventilation systems. The average PM_2.5 and CO₂ concentrations increased by 24.14% and 9.93% as the metro was driven from underground to overground. The average in-carriage PM_2.5 concentrations increased by 17.19% and CO₂ concentration decreased by 16.97% as the metro was driven from urban to the suburban area. It was found that PM_2.5 concentration is proportional to the on-board passenger number at a ratio of 0.4 μg/m³·passenger. A mass-balance model was developed to estimate the in-carriage PM_2.5 concentration under different driving conditions.     

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.     

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 replacement of engine powered vehicles by electric vehicles on energy consumption and CO2 emissions

This paper evaluates the impacts on energy consumption and carbon dioxide (CO₂) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO₂) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO₂ emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO₂ emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet.     

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.     

Carbon dioxide emissions from port container distribution: Spatial characteristics and driving factors

Port carbon dioxide (CO₂) emissions in China have become an ever-increasing public concern due to their significant impacts on human health and the environment. However, existing studies focus mainly on CO₂ emissions from vessels calling at the ports and cargo handling within the ports, paying little attention to the inland distribution networks. To fill this gap, this paper proposes an easily implemented method for calculating CO₂ emissions from port container distribution (PCD) and investigates their spatial characteristics and driving factors. By analyzing 30 container ports in China, the main findings are as follows. First, road transportation is the major contributor of CO₂ emissions from PCD due to the lack of rail and inland water transportation. Second, PCD carbon emissions exhibit significant local spatial clustering. That is, ports with similar geographical locations tend to present a similar pattern of PCD carbon emissions. Third, as suggested by the spatial Durbin model, PCD carbon emissions are negatively determined by local gross domestic product, number of port berths, but are positively determined by local tertiary industry value and highway freight volume, and waterway freight volume in both local and neighboring ports. These results provide empirical insights into cross-port collaboration in reducing PCD carbon 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.     

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.     

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.     

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.     

Development of a corrected average speed model for calculating carbon dioxide emissions per link unit on urban roads

The purpose of our study is to develop a “corrected average emission model,” i.e., an improved average speed model that accurately calculates CO₂ emissions on the road. When emissions from the central roads of a city are calculated, the existing average speed model only reflects the driving behavior of a vehicle that accelerates and decelerates due to signals and traffic. Therefore, we verified the accuracy of the average speed model, analyzed the causes of errors based on the instantaneous model utilizing second-by-second data from driving in a city center, and then developed a corrected model that can improve the accuracy. We collected GPS data from probe vehicles, and calculated and analyzed the average emissions and instantaneous emissions per link unit. Our results showed that the average speed model underestimated CO₂ emissions with an increase in acceleration and idle time for a speed range of 20 km/h and below, which is the speed range for traffic congestion. Based on these results, we analyzed the relationship between average emissions and instantaneous emissions according to the average speed per link unit, and we developed a model that performed better with an improved accuracy of calculated CO₂ emissions for 20 km/h and below.     

Examining transport futures with scenario analysis and MCA

Climate change is a global problem and across the world the transport sector is finding it difficult to break projected increases in carbon dioxide (CO₂) emissions; there are very few contexts where deep reductions in transport CO₂ emissions are being made. A number of research studies are now examining the potential for future lower CO₂ emissions in the transport sector. This paper develops this work to consider some of the wider sustainability impacts (economic, social and local environmental) as well as the lower CO₂ transport impacts of different policy trajectories. Hence the central argument made is for an integrated approach to transport policy making over the longer term - incorporating scenario analysis and multi-criteria assessment (MCA) - to help assess likely progress against a range of objectives.The analysis is based on work carried out in Oxfordshire, UK. Different packages of measures are selected and two scenarios developed which satisfy lower CO₂ aspirations, one of which also provides wider positive sustainability impacts. A simulation model has been produced to help explore the strategic policy choices and tensions evident for decision-makers involved in local transport planning. The paper argues for a ‘strategic conversation’ (Van der Heijden, 1996) at the sub-regional and city level, based upon future scenario analysis and MCA, discussing the priorities for intervention. Such an approach will help us examine the scale of change and trade-offs required in moving towards sustainable transport futures.     

The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems considering carbon dioxide emissions

Multi-echelon distribution strategy is primarily to alleviate the environmental (e.g., energy consumption and emissions) consequence of logistics operations. Differing from the long-term strategic problems (e.g., the two-echelon vehicle routing problem (2E-VRP), the two-echelon location routing problem (2E-LRP) and the truck and trailer routing problem (TTRP)) that make location decisions in depots or satellites, the paper introduces a short-term tactical problem named the two-echelon time-constrained vehicle routing problem in linehaul-delivery systems (2E-TVRP) considering carbon dioxide (CO₂) emissions. The linehaul level and the delivery level are linked through city distribution centers (CDCs). The 2E-TVRP, which takes CO₂ emissions per ton-kilometer as the objective, has inter-CDC linehaul on the 1st level and delivery from CDCs to satellites on the 2nd level. The Clarke and Wright savings heuristic algorithm (CW) improved by a local search phase is put forward. The case study shows the applicability of the model to real-life problems. The results suggest that the vehicle scheduling provided by the 2E-TVRP is promising to reduce the CO₂ emissions per ton-kilometer of the linehaul-delivery system. Adjusting the central depot location or developing the loaded-semitrailer demand among O-D pairs to eliminate empty-running of tractors will contribute to reduce the CO₂ emission factor.     

Factors affecting public transportation,car, and motorcycle usage

This study established a hypothesis model based on the seemingly unrelated regression equations (SURE) model to investigate the relationship between public transportation, car, and motorcycle use in various townships in Taiwan and to analyse important factors that affect the usage of these modes. The SURE model was adopted because of the lack of a significant correlation between the dependent variables. The pairwise covariance analysis for any two of the three transportation modes revealed that the transportation modes could substitute for one another. Factors related to modal and demographic characteristics had different impacts on the usage of the three modes. The calculation of elasticity using different population densities and public transportation usage showed that when the ‘number of city bus routes’ was increased by 50% in areas with high population density and high public transportation usage, car usage decreased by 1.4%, which corresponds to 300,000 vehicles, and total CO₂ emissions reduced by 0.0204%. When the ‘total length of city bus routes’ was increased by 50%, the number of motorcycles used decreased by 83 million, and total CO₂ emissions reduced by 1.119%, which corresponds to 1.4 million tonnes of CO₂ emission. These findings suggest that these different factors had varying impacts on car and motorcycle usage in different areas. We therefore recommended that future transportation policies consider the varying transportation usage trends in different areas.