The relative contribution of transportation to supply chain greenhouse gas emissions: A case study of American wheat

This life cycle assessment case study puts the supply chain contribution of transportation to greenhouse gas emissions in context with other contributors using American wheat grain as a representative product. Multiple locations, species and routes to market are investigated. Transportation contributes 39–56% of the supply chain emissions, whereas there is a 101% intra-species and 62% inter-species variation in greenhouse gas emissions from production, demonstrating that transportation is both of smaller magnitude, and less sensitive than other factors, in particular, field sequestration.     

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.     

Field investigation and parametric study of greenhouse gas emissions from railway plain-line renewals

Railway transportation is becoming increasingly important in many parts of the world for mass transport of passengers and freight. This study was prompted by the industry’s need to systemically estimate greenhouse gas emissions from railway construction and maintenance activities. In this paper, the emphasis is placed on plain-line railway maintenance and renewal projects. The objective of this study was to reduce the uncertainties and assumptions of previous studies based on ballasted track maintenance and renewal projects. A field-based data collection was carried out on plain-line ballasted track renewals. The results reveal that the emissions from the materials contribute more than nine times the CO₂-e emissions than the machines used in the renewal projects. The results show that extending the lifespan of rail infrastructure assets through maintenance is beneficial in terms of reducing CO₂-e emissions. Analysis was then carried out using the field data. Then the results were compared to two ballastless track alternatives. The results show that CO₂-e emissions per metre from ballasted track were the least overall, however, the maintenance CO₂-e emissions are greater than those of ballastless tracks over the infrastructure lifespan, with ballasted track maintenance emitting more CO₂-e emissions at the 30 and 60 year intervals and the end of life when compared to the ballastless track types. The outcome of the study can provide decision makers, construction schedulers, environmental planners and project planners with reasonably accurate GHG emission estimates that can be used to plan, forecast and reduce emissions for plain-line renewal projects.     

Evaluation of CO2 emissions from railway resurfacing maintenance activities

This paper is the world first to investigate the CO₂ impact of railway resurfacing in ballasted track bed maintenance. Railway resurfacing is an important routine maintenance activity that restores track geometry to ensure safety, reliability and utility of the asset. This study consisted of an extensive field data collection from resurfacing machineries (diesel-engine tamping machines, ballast regulators and ballast stabilisers) including travel distances, working distances, fuel consumption and construction methodologies. Fuel consumption was converted to a kg CO₂/m using the embodied energies of diesel. Analyses showed that tamping machines emitted the highest CO₂ emissions of the resurfacing machineries, followed by ballast regulators and ballast stabilisers respectively. Tamping machines processed 4.25 m of track per litre of diesel, ballast regulators processed 6.51 m of track per litre of diesel and ballast stabilisers processed 10.61 m of track per litre of diesel. The results were then compared to previous studies and a rigorous parametric study was carried out to consider long-term resurfacing CO₂ emissions on Australian railway track. The outcome of this study is unprecedented and it enables track engineers and construction managers to critically plan strategic rail maintenance and to develop environmental-friendly policies for track geometry and alignment restoration.     

The role of ‘indirect’ greenhouse gas emissions in tourism: Assessing the hidden carbon impacts from a holiday package tour

Tourism is a noticeable contributor to global greenhouse gas (GHG) emissions. Existing estimates of tourism’s carbon footprint are however incomplete as they fail to holistically assess the additional, ‘indirect’ carbon requirements. These arise from the non-use phases of a tourism product or service life cycle and can be further magnified by supply chain industries. Under-development of methods for carbon impact assessment in tourism is the primary reason for the omission of ‘indirect’ GHG emissions. This study develops a new approach for comprehensive appraisal of GHG emissions which incorporates and advances the methodological advantages of existing assessment techniques. It tests the applicability of this approach in tourism by conducting a holistic analysis of a standard holiday package to Portugal, based on the British tourism market. The new approach demonstrates the significance of the ‘indirect’ GHG emissions in the total carbon footprint from the holiday package, thus emphasising the necessity for more comprehensive future assessments.     

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.     

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.     

Life cycle assessment of High Speed Rail in China

China has built the world’s largest High Speed Rail (HSR) network. Its environmental impacts have been examined by the means of life cycle assessment (LCA) which describes the whole picture of the HSR system instead of single stages, with a case study for the high-speed railway that links Beijing and Shanghai. The research employs the China-specific life cycle inventory database Chinese Core Life Cycle Database (CLCD). Vehicle operation dominates most impact categories, while vehicle manufacturing/maintenance/disposal and infrastructure construction contribute mostly to mineral consumption (43% and 38%) and organic compounds in water (54% for infrastructure construction). Several scenarios are developed to explore effects of changes in HSR development, utilization, electricity mix, and infrastructure planning and construction. Suggestions are provided for improving the life cycle environmental performance of China’s HSR systems.     

The carbon footprint of business travel in the knowledge-intensive service sector

We explore the travel needs and patterns, and the corresponding carbon footprint, of small service organizations during different phases of knowledge-intensive business processes, and compare the results with the priorities given to travel-related goals by staff. We apply a combination of focus group data, mobile positioning, and individual follow-up interviews as study methods. The need for physical travel is determined by a combination of the perceived potential for knowledge creation and transfer offered by each trip, the strength of interpersonal relationships in business networks, and the significance of the travel goal in terms of economic sustainability. The priorities given to travel goals reflect the environmental load of business travel only in domestic contexts, where executing core business processes accounted for the highest carbon footprint. We propose the ways in which the management of business interactions could take into account sociotechnical environment and social recognition of low-carbon communication and travel modes.     

Estimating the CO2 intensity of intermodal freight transportation

This paper looks at the environmental effects of shifting from road to rail freight transportation. Little data is available to shippers to calculate the potential CO₂ savings of an intermodal shift. In this paper we analyze a data set of more than 400,000 intermodal shipments to calculate the CO₂ intensity of intermodal transportation as a distinct mode. Our results indicate an average intensity of 67 g of CO₂ per ton-mile, but can vary between 29 and 220 g of CO₂ per ton-mile depending on the specific origin–destination lane. We apply the market area concept to explain the variance between individual lane intensities and demonstrate the complexity in predicting the potential carbon savings in a switch from truckload to intermodal.     

Possibilistic fuel cycle assessment of retrofit technologies for two stroke powered tricycles

Two stroke powered tricycles are a major source of air pollution in the Philippines. A fuelcycle assessment of the liquefied petroleum gas (LPG) and direct injection retrofit technologies for these vehicles is conducted. The results when compared with carbureted two and four strokes units indicate that retrofitting the units to direct injection provides lower fossil energy depletion, global warming, human toxicity and photochemical ozone formation impact potentials compared to LPG fueled carbureted two stroke tricycles while the latter exhibits lower acidification and nutrification impact values. The direct injection retrofitted units show a lower aggregated impact score and dominance over four stroke units. The conversion to LPG revealed minimal environmental benefits compared to the gasoline run units.     

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.     

A comparative life-cycle energy and emissions analysis for intercity passenger transportation in the U.S. by aviation,intercity bus,and automobile

Intercity passenger trips constitute a significant source of energy consumption, greenhouse gas emissions, and criteria pollutant emissions. The most commonly used city-to-city modes in the United States include aircraft, intercity bus, and automobile. This study applies state-of-the-practice models to assess life-cycle fuel consumption and pollutant emissions for intercity trips via aircraft, intercity bus, and automobile. The analyses compare the fuel and emissions impacts of different travel mode scenarios for intercity trips ranging from 200 to 1600 km. Because these modes operate differently with respect to engine technology, fuel type, and vehicle capacity, the modeling techniques and modeling boundaries vary significantly across modes. For aviation systems, much of the energy and emissions are associated with auxiliary equipment activities, infrastructure power supply, and terminal activities, in addition to the vehicle operations between origin/destination. Furthermore, one should not ignore the embodied energy and initial emissions from the manufacturing of the vehicles, and the construction of airports, bus stations, highways and parking lots. Passenger loading factors and travel distances also significantly influence fuel and emissions results on a per-traveler basis. The results show intercity bus is generally the most fuel-efficient mode and produced the lowest per-passenger-trip emissions for the entire range of trip distances examined. Aviation is not a fuel-efficient mode for short trips (<500 km), primarily due to the large energy impacts associated with takeoff and landing, and to some extent from the emissions of ground support equipment associated with any trip distance. However, aviation is more energy efficient and produces less emissions per-passenger-trip than low-occupancy automobiles for trip distances longer than 700–800 km. This study will help inform policy makers and transportation system operators about how differently each intercity system perform across all activities, and provides a basis for future policies designed to encourage mode shifts by range of service. The estimation procedures used in this study can serve as a reference for future analyses of transportation scenarios.     

Spatio-temporal analysis of car distance,greenhouse gases and the effect of built environment: A latent class regression analysis

This work examines the temporal–spatial variations of daily automobile distance traveled and greenhouse gas emissions (GHGs) and their association with built environment attributes and household socio-demographics. A GHGs household inventory is determined using link-level average speeds for a large and representative sample of households in three origin–destination surveys (1998, 2003 and 2008) in Montreal, Canada. For the emission inventories, different sources of data are combined including link-level average speeds in the network, vehicle occupancy levels and fuel consumption characteristics of the vehicle fleet. Urban form indicators over time such as population density, land use mix and transit accessibility are generated for each household in each of the three waves. A latent class (LC) regression modeling framework is then implemented to investigate the association of built environment and socio-demographics with GHGs and automobile distance traveled. Among other results, it is found that population density, transit accessibility and land-use mix have small but statistically significant negative impact on GHGs and car usage. Despite that this is in accordance with past studies, the estimated elasticities are greater than those reported in the literature for North American cities. Moreover, different household subpopulations are identified in which the effect of built environment varies significantly. Also, a reduction of the average GHGs at the household level is observed over time. According to our estimates, households produced 15% and 10% more GHGs in 1998 and 2003 respectively, compared to 2008. This reduction can be associated to the improvement of the fuel economy of vehicle fleet and the decrease of motor-vehicle usage – e.g., a decrease of 4% is observed for fuel efficiency rates and 12% for distance according to the raw average estimates from 1998 with respect to 2008. A strong link is also observed between socio-demographics and the two travel outcomes. While number of workers is positively associated with car distance and GHGs, low and medium income households pollute less than high-income households.     

Decomposition analysis of energy-related carbon emissions from the transportation sector in Beijing

In the process of rapid development and urbanization in Beijing, identifying the potential factors of carbon emissions in the transportation sector is an important prerequisite to controlling carbon emissions. Based on the expanded Kaya identity, we built a multivariate generalized Fisher index (GFI) decomposition model to measure the influence of the energy structure, energy intensity, output value of per unit traffic turnover, transportation intensity, economic growth and population size on carbon emissions from 1995 to 2012 in the transportation sector of Beijing. Compared to most methods used in previous studies, the GFI model possesses the advantage of eliminating decomposition residuals, which enables it to display better decomposition characteristics (Ang et al., 2004). The results show: (i) The primary positive drivers of carbon emissions in the transportation sector include the economic growth, energy intensity and population size. The cumulative contribution of economic growth to transportation carbon emissions reaches 334.5%. (ii) The negative drivers are the transportation intensity and energy structure, while the transportation intensity is the main factor that restrains transportation carbon emissions. The energy structure displays a certain inhibition effect, but its inhibition is not obvious. (iii) The contribution rate of the output value of per unit traffic turnover on transportation carbon emissions appears as a flat “M”. To suppress the growth of carbon emissions in transportation further, the government of Beijing should take the measures of promoting the development of new energy vehicles, limiting private vehicles’ increase and promoting public transportation, evacuating non-core functions of Beijing and continuingly controlling population size.     

Cost-effectiveness of reductions in greenhouse gas emissions from High-Speed Rail and urban transportation projects in California

A rising trend in state and federal transportation finance is to invest capital dollars into projects which reduce greenhouse gas (GHG) emissions. However, a key metric for comparing projects, the cost-effectiveness of GHG emissions reductions, is highly dependent on the cost-benefit methodology employed in the analysis. Our analysis comparing California High-Speed Rail and three urban transportation projects shows how four different accounting framings bring wide variations in cost per metric tonne of GHG emissions reduced. In our analysis, life-cycle GHG emissions are joined with full cost accounting to better understand the benefits of cap-and-trade investments. Considering only public subsidy for capital, none of the projects appear to be a cost-effective means to reduce GHG emissions (i.e., relative to the current price of GHG emissions in California’s cap-and-trade program at $12.21 per tonne). However, after adjusting for the change in private costs users incur when switching from the counterfactual mode (automobile or aircraft) to the mode enabled by the project, all investments appear to reduce GHG emissions at a net savings to the public. Policy and decision-makers who consider only the capital cost of new transportation projects can be expected to incorrectly assess alternatives and indirect benefits (i.e., how travelers adapt to the new mass transit alternative) should be included in decision-making processes.     

A method to measure the eco-efficiency of diesel locomotive

Brazilian railroads transport over 490 million tons a year using diesel-electric locomotives. These locomotives emit several pollutants into the atmosphere and because of that, the railroads seek to reduce emissions and achieve global emission standards. Thus, it is important to analyze the environmental impact of the use of diesel and alternative fuels to reach environmental standards. This paper makes use of a method based upon the World Business Council for Sustainable Development (WBCSD) metrics to evaluate the locomotives’ eco-efficiency. The method was applied to Estrada de Ferro Vitória a Minas (EFVM). Different scenarios representing the exchange of fuel sources and technologies were developed, tested and analyzed. The impacts were evaluated by seven eco-efficiency performance indicators and compared with United States Environmental Protection Agency (EPA) standards. The results offered cost savings and emissions reduction opportunities.     

Traffic modelling in system boundary expansion of road pavement life cycle assessment

This paper uses a case study of a UK inter-urban road, to explore the impact of extending the system boundary of road pavement life cycle assessment (LCA) to include increased traffic emissions due to delays during maintenance. Some previous studies have attempted this but have been limited to hypothetical scenarios or simplified traffic modelling, with no validation or sensitivity analysis. In this study, micro-simulation modelling of traffic was used to estimate emissions caused by delays at road works, for several traffic management options. The emissions were compared to those created by the maintenance operation, estimated using an LCA model. In this case study, the extra traffic emissions caused by delays at road works are relatively small, compared to those from the maintenance process, except for hydrocarbon emissions. However, they are generally close to, or above, the materiality threshold recommended in PAS2050 for estimating carbon footprints, and reach 5–10% when traffic flow levels are increased (hypothetically) or when traffic management is imposed outside times of lowest traffic flow. It is recommended, therefore, that emissions due to traffic disruption at road works should be included within the system boundary of road pavement LCA and carbon footprint studies and should be considered in developing guidelines for environmental product declarations of road pavement maintenance products and services.     

Pathways for GHG emission reduction in Norwegian road transport sector: Perspective on consumption of passenger car transport and electricity mix

Electrification of the transport sector is considered as a solution to reduce greenhouse gases (GHGs) emissions and achieve sustainable mobility. Specifically in the case of electrification of passenger vehicles, various industrial and policy initiatives have been introduced. In this article, we present and assess three approaches – pro-technology, pro-simplicity and mix (of the aforementioned approaches) – to achieve target emission reductions in the Norwegian road transport sector. We also assess the influence of including ‘Guarantee of Origin’ certification for the electricity production in accounting for typical consumption electricity mix in Norway.Results show that for the same reductions in tail-pipe GHG emissions, pro-technology, pro-simplicity, and the mix scenario offer 22%, 29% and 28% reduction in the life cycle GHG emissions respectively, compared to the reference scenario in year 2020. However, the pro-simplicity scenario requires 25% reduction in vehicle-km driven compared to the pro-technology scenario, which provides the same passenger car mobility as in the reference case. When the GHG intensity of the electricity mix used to power EVs is corrected to account for actual consumption mix in Norway, a 13% reduction in the net GHG benefit of pro-technology scenario is observed.     

A network-based dispatch model for evaluating the spatial and temporal effects of plug-in electric vehicle charging on GHG emissions

The well-to-wheel emissions associated with plug-in electric vehicles (PEVs) depend on the source of electricity and the current non-vehicle demand on the grid, thus must be evaluated via an integrated systems approach. We present a network-based dispatch model for the California electricity grid consisting of interconnected sub-regions to evaluate the impact of growing PEV demand on the existing power grid infrastructure system and energy resources. This model, built on a linear optimization framework, simultaneously considers spatiality and temporal dynamics of energy demand and supply. It was successfully benchmarked against historical data, and used to determine the regional impacts of several PEV charging profiles on the current electricity network. Average electricity carbon intensities for PEV charging range from 244 to 391 gCO₂e/kW h and marginal values range from 418 to 499 gCO₂e/kW h.