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.     

Fuel cycle emissions and life cycle costs of alternative fuel vehicle policy options for the City of Houston municipal fleet

Municipal fleet vehicle purchase decisions provide a direct opportunity for cities to reduce emissions of greenhouse gases (GHG) and air pollutants. However, cities typically lack comprehensive data on total life cycle impacts of various conventional and alternative fueled vehicles (AFV) considered for fleet purchase. The City of Houston, Texas, has been a leader in incorporating hybrid electric (HEV), plug-in hybrid electric (PHEV), and battery electric (BEV) vehicles into its fleet, but has yet to adopt any natural gas-powered light-duty vehicles. The City is considering additional AFV purchases but lacks systematic analysis of emissions and costs. Using City of Houston data, we calculate total fuel cycle GHG and air pollutant emissions of additional conventional gasoline vehicles, HEVs, PHEVs, BEVs, and compressed natural gas (CNG) vehicles to the City's fleet. Analyses are conducted with the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model. Levelized cost per kilometer is calculated for each vehicle option, incorporating initial purchase price minus residual value, plus fuel and maintenance costs. Results show that HEVs can achieve 36% lower GHG emissions with a levelized cost nearly equal to a conventional sedan. BEVs and PHEVs provide further emissions reductions, but at levelized costs 32% and 50% higher than HEVs, respectively. CNG sedans and trucks provide 11% emissions reductions, but at 25% and 63% higher levelized costs, respectively. While the results presented here are specific to conditions and vehicle options currently faced by one city, the methods deployed here are broadly applicable to informing fleet purchase decisions.     

Meeting an 80% reduction in greenhouse gas emissions from transportation by 2050: A case study in California

This paper investigates how California may reduce transportation greenhouse gas emissions 80% below 1990 levels by 2050 (i.e., 80in50). A Kaya framework that decomposes greenhouse gas emissions into the product of population, transport intensity, energy intensity, and carbon intensity is used to analyze emissions and mitigation options. Each transportation subsector, including light-duty, heavy-duty, aviation, rail, marine, agriculture, and off-road vehicles, is analyzed to identify specific mitigation options and understand its potential for reducing greenhouse gas emissions. Scenario analysis shows that, while California’s 2050 target is ambitious, it can be achieved in transport if a concerted effort is made to change travel behavior and the vehicles and fuels that provide mobility. While no individual ‘‘Silver Bullet” strategy exists that can achieve the goals, a portfolio approach that combines strategies could yield success. The 80in50 scenarios show the impacts of advanced vehicle and fuels technologies as well as the role of travel demand reduction, which can significantly reduce energy and resource requirements and the level of technology development needed to meet the target.     

Time-based life-cycle assessment for environmental policymaking: Greenhouse gas reduction goals and public transit

As decision-makers increasingly embrace life-cycle assessment (LCA) and target transportation services for regional environmental goals, it becomes imperative that outcomes from changes to transportation infrastructure systems are accurately estimated. Greenhouse gas (GHG) reduction policies have created interest in better understanding how public transit systems reduce emissions. Yet the use of average emission factors (e.g., grams CO₂e per distance traveled) persists as the state-of-the-art masking the variations in emissions across time, and confounding the ability to accurately estimate the environmental effects from changes to transit infrastructure and travel behavior. An LCA is developed of the Expo light rail line and a competing car trip (in Los Angeles, California) that includes vehicle, infrastructure, and energy production processes, in addition to propulsion. When results are normalized per passenger kilometer traveled (PKT), life-cycle processes increase energy use and GHG emissions up to 83%, and up to 690% for smog and respiratory impact potentials. However, the use of a time-independent PKT normalization obfuscates a decision-maker’s ability to understand whether the deployment of a transit system reduces emissions below a future year policy target (e.g., 80% of 1990 emissions by 2050). The year-by-year marginal effects of the decision to deploy the Expo line are developed including reductions in automobile travel. The time-based marginal results provide clearer explanations for how environmental effects in a region change and the critical life-cycle processes that should be targeted to achieve policy targets. It shows when environmental impacts payback and how much reduction is achieved by a policy-specified future year.     

Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.     

Can regional transportation and land-use planning achieve deep reductions in GHG emissions from vehicles?

The Intergovernmental Panel on Climate Change estimates that greenhouse gas emissions (GHG) must be cut 40–70% by 2050 to prevent a greater than 2 °Celsius increase in the global mean temperature; a threshold that may avoid the most severe climate change impacts. Transportation accounts for about one third of GHG emissions in the United States; reducing these emissions should therefore be an important part of any strategy aimed at meeting the IPCC targets. Prior studies find that improvements in vehicle energy efficiency or decarbonization of the transportation fuel supply would be required for the transportation sector to achieve the IPCC targets. Strategies that could be implemented by regional transportation planning organizations are generally found to have only a modest GHG reduction potential. In this study we challenge these findings. We evaluate what it would take to achieve deep GHG emission reductions from transportation without advances in vehicle energy efficiency and fuel decarbonization beyond what is currently expected under existing regulations and market expectations. We find, based on modeling conducted in the Albuquerque, New Mexico metropolitan area that it is possible to achieve deep reductions that may be able to achieve the IPCC targets. Achieving deep reductions requires changes in transportation policy and land-use planning that go far beyond what is currently planned in Albuquerque and likely anywhere else in the United States.     

Greenhouse gas emission benefits of vehicle lightweighting: Monte Carlo probabalistic analysis of the multi material lightweight vehicle glider

Vehicle lightweighting reduces fuel cycle greenhouse gas (GHG) emissions but may increase vehicle cycle (production) GHG emissions because of the GHG intensity of lightweight material production. Life cycle GHG emissions are estimated and sensitivity and Monte Carlo analyses conducted to systematically examine the variables that affect the impact of lightweighting on life cycle GHG emissions. The study uses two real world gliders (vehicles without powertrain or battery) to provide a realistic basis for the analysis. The conventional and lightweight gliders are based on the Ford Fusion and Multi Material Lightweight Vehicle, respectively. These gliders were modelled with internal combustion engine vehicle (ICEV), hybrid electric vehicle (HEV), and battery electric vehicle (BEV) powertrains. The probability that using the lightweight glider in place of the conventional (steel-intensive) glider reduces life cycle GHG emissions are: ICEV, 100%; HEV, 100%, and BEV, 74%.The extent to which life cycle GHG emissions are reduced depends on the powertrain, which affects fuel cycle GHG emissions. Lightweighting an ICEV results in greater base case GHG emissions mitigation (10 t CO₂eq.) than lightweighting a more efficient HEV (6 t CO₂eq.). BEV lightweighting can result in higher or lower GHG mitigation than gasoline vehicles, depending largely on the source of electricity.     

Eco-driver training within the City of Calgary’s municipal fleet: Monitoring the impact

This article highlights eco-driving as an available policy option to reduce climate altering GHG emissions. Recognizing the need to reduce the environmental impact of its fleet operations, the City of Calgary is a leader in developing programs and policies that aim to reduce GHG emissions and associated pollutants resulting from the use of fossil fuels. Among local action taken against climate change, the City sought to quantify CO₂ emissions reductions from their municipal fleet as a result of eco-driver training, with a specific focus on engine idling. Fifteen drivers from the Development & Building Approvals Business Unit had in-vehicle monitoring technology (CarChips®) installed into their vehicles as part of a three-phase research process. The results show that gasoline and hybrid vehicles decreased average idling between 4% and 10% per vehicle per day, leading to an average emissions decrease of 1.7 kg of CO₂ per vehicle per day.     

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.     

Electric vehicles for greenhouse gas reduction in China: A cost-effectiveness analysis

There have been ongoing debates over whether battery electric vehicles contribute to reducing greenhouse gas emissions in China’s context, and if yes, whether the greenhouse gas emissions reduction compensates the cost increment. This study informs such debate by examining the life-cycle cost and greenhouse gas emissions of conventional vehicles, hybrid electric vehicles and battery electric vehicles, and comparing their cost-effectiveness for reducing greenhouse gas emissions. The results indicate that under a wide range of vehicle and driving configurations (range capacity, vehicle use intensity, etc.), battery electric vehicles contribute to reducing greenhouse gas emissions compared with conventional vehicles, although their current cost-effectiveness is not comparable with hybrid electric vehicles. Driven by grid mix optimization, power generation efficiency improvement, and battery cost reduction, the cost-effectiveness of battery electric vehicles is expected to improve significantly over the coming decade and surpass hybrid electric vehicles. However, considerable uncertainty exists due to the potential impacts from factors such as gasoline price. Based on the analysis, it is recommended that the deployment of battery electric vehicles should be prioritized in intensively-used fleets such as taxis to realize high cost-effectiveness. Technology improvements both in terms of power generation and vehicle electrification are essential in improving the cost-effectiveness of battery electric vehicles.     

Road transport and climate change: Stepping off the greenhouse gas

Transport is Australia’s third largest and second fastest growing source of greenhouse gas (GHG) emissions. The road transport sector makes up 88% of total transport emissions and the projected emissions increase from 1990 to 2020 is 64%. Achieving prospective emission reduction targets will pose major challenges for the road transport sector. This paper investigates two targets for reducing Australian road transport greenhouse gas emissions, and what they might mean for the sector: emissions in 2020 being 20% below 2000 levels; and emissions in 2050 being 80% below 2000 levels. Six ways in which emissions might be reduced to achieve these targets are considered. The analysis suggests that major behavioural and technological changes will be required to deliver significant emission reductions, with very substantial reductions in vehicle emission intensity being absolutely vital to making major inroads in road transport GHG emissions.     

Life cycle emissions and cost model for urban light duty vehicles

The growth of vehicle sales and use internationally requires the consumption of significant quantities of energy and materials, and contributes to the deterioration of air-quality and climate conditions. Advanced propulsion systems and electric drive vehicles have substantially different characteristics and impacts. They require life cycle assessments and detailed comparisons with gasoline powered vehicles which, in turn, should lead to critical updates of traditional models and assumptions. For a comprehensive comparison of advanced and traditional light duty vehicles, a model is developed that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Life cycle emissions and time losses are converted into costs for seven urban light duty vehicles. The results, which are based on vehicle technology characteristics and transportation impacts on environment, facilitate vehicle comparisons and support policy making in transportation. Substantially, more sustainable urban transportation can be achieved in the short-term by promoting policies that increase vehicle occupancy; in the intermediate-term by increasing the share of hybrid vehicles in the car market and in the long-term by the widespread use of electric vehicles. A sensitivity-analysis of life cost results revealed that vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power and pollution. Current practices in carbon and air quality pricing favor oil and coal based technologies. However, increasing the cost of electricity from coal and other fossil fuels would increase the variable cost for electric vehicles, and tend to favor the variable cost of hybrid vehicles.     

Impact of convenient away-from-home charging infrastructure

This work uses market analysis and simulation to explore the potential impact of workplace and similarly convenient away-from-home charging infrastructure (CAFHCI) in reducing US light duty vehicle (LDV) petroleum use and greenhouse gas emissions. The ParaChoice model simulates the evolution of LDV sales, fuel use, and emissions through 2050, considering consumer responses to different options of electric range extension made available through CAFHCI, fraction of the population with access, and delay in infrastructure implementation. Results indicate that providing a greater fraction of the population access to CAFHCI at level 1 charging rates for a full workday (∼16–20 miles of range extension) may lead to more petroleum use reduction than providing level 2 charging to a lesser fraction. This result holds even considering the fraction of the population without at-home charging. 2050 battery electric vehicle sales increase 40% (85%) if the entire population is guaranteed daily access to one full workday of level 1 CAFHCI (half a workday of level 2, ∼80 miles of range extension). Plug-in hybrid sales increase when CAFHCI enables range extension below 20–40 miles/day, most significantly in households without at-home charging capability. Faster CAFHCI may decrease plug-in hybrid sales as less expensive BEVs become attractive to a greater fraction of the market.     

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

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

Greenhouse gas emissions associated with electric vehicle charging: The impact of electricity generation mix in a developing country

Since 2012, the government has been promoting the electric vehicles and the development of related infrastructure to encourage local automakers to explore into the alternatively powered vehicles. However, the benefits of grid-dependent EVs can only be harvested under the condition that their use is coupled with a low carbon electricity grid. Thus, it is an additional challenge for Malaysia's that are largely dependent on fossil fuels for electricity generation. The object of this paper is to perform a well-to-wheel life cycle assessment for calculating the greenhouse gas emissions attributable to the usage of ICEVs, HEVs and EVs in Malaysian scenario. These emission calculations will provide the best information for policymakers, researchers, and investors to make appropriate and effective decisions on policies, research and investments in future transport energy. The results show that running EVs with national grid will produce an average of 7% more GHG emissions than HEVs at the same distance. However, they will produce an average of 19% less GHG emissions than the ICEVs. Overall the GHG emissions produced through the usage of EVs are substantial based on the well-to-wheel analysis, as the environmental profile of EVs is linked with the national grid. Therefore, in order to harvest the benefit of EVs towards climate change and global warming mitigation, massive modernization and transformation should be taken for the development of the national grid towards greener sources.     

Just-in-time delivery for green fleets: A feedback control approach

With increasing attention being paid to greenhouse gas (GHG) emissions, the transportation industry has become an important focus of approaches to reduce GHG emissions, especially carbon dioxide equivalent (CO₂e) emissions. In this competitive industry, of course, any new emissions reduction technique must be economically attractive and contribute to good operational performance. In this paper, a continuous-variable feedback control algorithm called GEET (Greening via Energy and Emissions in Transportation) is developed; customer deliveries are assigned to a fleet of vehicles with the objective function of Just-in-Time (JIT) delivery and fuel performance metrics akin to the vehicle routing problem with soft time windows (VRPSTW). GEET simultaneously determines vehicle routing and sets cruising speeds that can be either fixed for the entire trip or varied dynamically based on anticipated performance. Dynamic models for controlling vehicle cruising speed and departure times are proposed, and the impact of cruising speed on JIT performance and fuel performance are evaluated. Allowing GEET to vary cruising speed is found to produce an average of 12.0–16.0% better performance in fuel cost, and −36.0% to +16.0% discrepancy in the overall transportation cost as compared to the Adaptive Large Neighborhood Search (ALNS) heuristic for a set of benchmark problems. GEET offers the advantage of extremely fast computational times, which is a substantial strength, especially in a dynamic transportation environment.     

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.     

Assessing carbon reduction effects toward the mode shift of green transportation system

Plans are underway to introduce green transportation systems at Taiwan's famous scenic spot, Sun Moon Lake, to reduce carbon emissions. Carbon reduction effects after changing the current lake tour modes are assessed using a nested logit model with a stated preference survey, which investigated tourists' choice preferences. The empirical results reveal that the modes of electric bus, electric vehicle sharing, and bike are clustered in the same competitive group. Travel cost, in‐vehicle travel time, and out‐vehicle travel time are found to be statistically significant with the expected negative effects. In particular, the attribute of carbon reduction is only significant for green tourists, who are willing to pay US$ 3.5/kg of carbon saved. The result indicates that more efficient carbon reduction is possible by restricting the usage of gasoline vehicles rather than improving the service levels of low‐carbon modes. Notably, the effect of parking charges on emission reduction is equal to the amount of carbon dioxide absorbed by 4511 trees per day. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Greenhouse gas reduction potential of advanced traffic control

Reducing greenhouse gas (GHG) emissions from transportation in the context of the climate change issue and the associated Kyoto Agreement of 1997 is a challenge. Since urban transportation is a major contributor to greenhouse gases, measures are required to reduce these emissions. Given that during peak periods, road vehicles propelled by petroleum fuel‐based internal combustion engines produce a high level of GHG emissions due to stop and go operations, measures to improve traffic flow can play an effective mitigation role. This paper describes a simulation‐based methodology and a case study for the quantification of GHG emission reduction owing to advanced traffic control systems.