Analysis of greenhouse gas emissions of freight transport sector in China

Due to the increasing commercial activities in China, the rapid growth of energy consumption and greenhouse gas (GHG) emissions in the freight transport sector has alarmed the Chinese central government. However, there is a lack of standard measure for evaluating GHG emissions generated from freight transport operations. To improve this situation, Chinese policy makers need to evaluate GHG emissions for energy saving and pollution reduction. This background leads us to examine the GHG emission trajectories and features of Chinese freight transport patterns in the last decade, i.e. between 2000 and 2011. In this study, we examine different regions’ freight turnover and energy consumption by various transport modes (i.e. railway, highway, waterway, aircraft, and oil pipeline) in China. Our results show that the total amount of GHG emissions caused by the Chinese freight transport sector reached 978 million tons in 2011, indicating an average annual growth of 74 million tons CO₂e for the last decade. Shandong, Anhui, and Henan are the main provinces producing GHG emissions, representing 11.7%, 10.3%, and 10% of total emissions generated from the freight transport sector in China, respectively. This study also compares the regional GHG emissions from different freight transport modes including railway, highway, waterway, air transport, and oil pipeline. Based on the findings, policy implications are provided on how to mitigate freight transport emissions among different Chinese regions.     

Assessing greenhouse gas emissions from electric vehicle operation in Australia using temporal vehicle charging and electricity emission characteristics

ABSTRACT

Significant interest exists in the potential for electric vehicles (EVs) to be a source of greenhouse gas (GHG) abatement. In order to establish the extent to which EVs will deliver abatement, however, a realistic understanding of the electricity and transport sector GHG emissions impacts arising from different approaches to integrating EVs into the power system is required. A key issue in this regard is the extent to which GHG emissions are a function of where and when EV charging will be enabled (or disabled) by the provision of recharging infrastructure and implementation of charging management strategies by the electricity industry. This article presents an investigation of the GHG emissions arising from electricity and gasoline consumption by plug-in hybrid EVs under a range of standard EV-power system integration scenarios. An assessment framework is presented, and GHG emissions from EV use are assessed for the New South Wales (NSW) and South Australian (SA) pools of the Australian National Electricity Market (NEM) using retrospective electricity system generation data for 2011. Results highlight that there is a range of possible outcomes depending on the integration scenario and emissions accounting approach used. This range illustrates value of a temporally explicit assessment approach in capturing the temporal alignment of electricity sector emission intensity and EV charging. Results also show the importance of a clean electricity generation mix in order for EVs to provide a GHG abatement benefit beyond what would be achieved by a hybrid (but non-plug-in) vehicle. The extent to which overnight charging in NSW is observed to produce higher emissions relative to unmanaged charging also illustrates a possible trade-off between GHG emissions and benefits for electricity industry from EV charging at times of low demand.     

Greenhouse gas impacts of different modality style classes using latent class travel behavior model

This study analyzed the interconnections between urban structure and socioeconomic, demographic and lifestyle variables and direct ground transport greenhouse gas (GHG) emissions in the Helsinki metropolitan region in Finland by using a latent class choice model (LCCM). The aim of the study was to identify and improve our understanding of the latent modality styles which guide people's everyday travel choices, and the resulting GHG implications. The GHG implications for different modality style groups are particularly interesting, since such analysis has not been included in previous studies. This study used the transport survey of the Helsinki Region Transport (HSL) from 2012, including over 17,000 trips, and consisted of two parts: first, the population was divided into classes based on latent class analysis, and secondly, the mode choices and GHG emissions were modelled for each class. Seven modality style groups were defined with strongly varying GHG impacts and travel profiles. According to the class specific choice modelling the probabilities of selecting different modes also varied significantly. The study offers new information for designing effective mitigation policies for different types of modality style groups. For example, car-oriented groups would benefit from more fuel-efficient vehicles and vehicles with alternative power sources, whereas the multimodal traveler could be more receptive to policies promoting cycling and public transport. Overall, the study depicts the potential of the latent class method to study the emissions caused by heterogeneous populations and to search for efficient GHG mitigation possibilities.     

A fuel surcharge policy for reducing road traffic greenhouse gas emissions

This paper proposes a car pricing policy based on fuel surcharges in substitution of car ownership taxes for reducing greenhouse gas emissions by cars. The aim of the proposed policy is to change some (fixed) costs of car use that are not perceived at each trip into (variable) costs. The amount of fuel surcharges and the effects of their application on fuel consumption and on GHG emissions are estimated by a model that is able to relate gasoline and diesel consumption with fuel prices. The effects of the proposed policy on fuel consumption and on GHG emissions are estimated for Italy. The results show that car users prefer to shift towards more efficient fuel vehicles than to public transport, producing a significant, but less than expected, reduction of GHG emissions.     

A method for the estimation of greenhouse gas emissions based on road geometric design and its application to South Korea

South Korea has the tenth highest greenhouse gas (GHG) emissions worldwide, of which 16% originates from the road sector. Existing estimation methods of road GHG emissions have various limitations, such as low accuracy or the ability to only estimate GHG emissions within a limited area. Therefore, this study aimed to develop a methodology to estimate GHG emissions while considering various geometric designs of roads, including both vertical and horizontal alignment. The developed method is more objective and reliable than existing methodologies that consider only vertical alignment. First, Lamm's theory on travel speed profiles was applied to predict GHG emissions. Then, this study attempted to overcome the limited spatial estimation capacity of existing methods by considering upstream and downstream geometric design parameters simultaneously. Second, this study used the GHG operation mode extracted from the MOtor Vehicle Emission Simulator (MOVES), a modeling system that estimates emissions for mobile sources at the national, county, and project levels for criteria air pollutants, GHGs, and air toxicity. The operation mode includes vehicle type, fuel, and other factors, and is designed to estimate GHG emissions at 1-s intervals. Based on the results of the analysis, the effectiveness of the new method was compared to existing methods using an economic analysis (e.g., cost–benefits from the reduced emissions). This study presents a method for performing sensitive estimations of GHG emissions according to the geometric design of roads, which can be used to collect more accurate data on GHG emissions.     

Reprint of “Green supply chain decisions – Case-based performance analysis from the food industry”

Environmental impacts, such as GHC emissions, have been introduced to supply chain management as an additional parameter to traditional cost, lead-time and on-time delivery. Supply chain management represents a significant source of decisions affecting the eco-efficiency of many products. This paper analyses cases from the food industry, mainly order-picking, transportation, warehousing, and distribution aspects from the greening point of view. Three case examples of decisions in supply chain design in the food industry are considered. The results show dependencies between performance measures. Finally, a framework of decisions and their impact on performance is presented.     

The Trucking Sector Optimization Model: A tool for predicting carrier and shipper responses to policies aiming to reduce GHG emissions

In response to the growing Climate Change problem, governments around the world are seeking to reduce the greenhouse gas (GHG) emissions of trucking. The Trucking Sector Optimization (TSO) model is introduced as a tool for studying the decisions that shippers and carriers make throughout time (focusing on investments in Fuel Saving Technologies), and for evaluating their impact on life-cycle GHG emissions. A case study of fuel taxation in California is used to highlight the importance of (1) modeling the trucking sector comprehensively, (2) modeling the dynamics of the stock of vehicles, and (3) modeling different sources of emissions.     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

Life-cycle CO2 emissions and influential factors for asphalt highway construction and maintenance activities in China

This study tried to clarify the magnitude of CO₂ emissions from highway construction and maintenance in China through life cycle assessment (LCA) method. For this, 227 real highway projects constructed from the year 2000 to 2011 in Zhejiang Province, China are classified into six types by two categories of N road (62 projects without grand bridge, great bridge and tunnel) and Y road (165 projects with the same road structures) and three sub-categories of (i) newly constructed road, (ii) replacing pavement road and (iii) full rehabilitated road. Significant influential factors of LCA results were revealed through multivariate linear regression models, combined with data quality assessment and sensitivity analysis. Numerical interval of assessment results indicate that the construction emissions of N highway project are more centralized to no more than 2900 t/lane-km, while Y project have a normal upper boundary of construction CO₂ emissions, about 5000 t/lane-km. The contribution of maintenance to CO₂ emissions probably could exceed that of newly construction both for Y project and N project. In addition, the pavement replacing and rehabilitation could bring about large amount of CO₂ emissions which even match with the CO₂ emissions from cumulative traffic volume during highway's life cycle. There are common factors for six categories. Cement and steel are the top largest CO₂ emissions contributors and sensitive factors for N road and Y road. The LCA results are not sensitive to the local construction materials but sensitive to the emission factor of diesel used in transportation and on-site construction.     

Greenhouse gas emissions from flying can offset the gain from reduced driving in dense urban areas

Numerous studies have illustrated how denser urban forms lead to smaller greenhouse gas (GHG) emissions from passenger transport. Many of these studies have excluded aviation since the association between urban structure and air travel is not as intuitive as it is the case of ground travel. However, several recent studies have concluded that air travel is a significant contributor to the GHGs from passenger transport. Furthermore, even air travel habits depend heavily on lifestyles and socio-economic factors that are related to the urban form. Here we analyse the interactions between urban structure and different transportation modes and their GHG impacts in Finland. The study utilises the data from the Finnish Transportation Agency’s passenger traffic survey from May 2010 to May 2011, which includes over 12 000 people and over 35 000 trips. The survey is based on one-day travel diaries and also includes additional data on long-distance trips from a longer period. Methodologically, the study takes a traveller’s perspective to assess the GHG emissions from passenger transport. We found that (1) air travel breaks the pattern where GHG emissions decrease with increasing density of urban structures, and (2) in the metropolitan region there is a clear trade-off between car-ownership and air travel in the middle income class. The main policy implication of our study is that air travel must be included in GHG assessments and mitigation strategies targeting travel behaviour. In dense urban regions, the emissions of air travel have the potential to offset the gain from reduced private driving.     

Green accessibility: Estimating the environmental costs of network-time prisms for sustainable transportation planning

Accessibility, or the ease to participate in activities and obtain resources in a given environment, is crucial for evaluating transportation systems. Greater accessibility is often achieved by increasing individuals' potential mobility. However, potential mobility, if realized by motorized modes, can also generate negative environmental impacts such as fossil fuel consumption and greenhouse gas (GHG) emissions. While the negative environmental impacts of greater mobility are acknowledged, there has been a lack of research to validate those impacts using empirical data, especially considering variations in individuals' mobility levels. This paper presents a method for estimating the expected environmental costs of accessibility represented by a network-time prism (NTP). A NTP delimits all accessible locations within a network and the available time for an individual to present at each location given a scheduled trip origin and destination, a time budget and the maximum achievable speeds along network edges. Estimating the expected environmental costs of a NTP involves three steps: (1) semi-Markov techniques to simulate the probabilities to move along network edges at given times; (2) the speed profiles for reachable edges, and (3) a cost function that translates speeds into environmental impacts. We focus on air quality and employ the motor vehicle emission simulator MOVESLite to estimate the CO₂ emissions at both the edge and prism levels. We calibrate and validate the methods for experimental NTPs defined within the Phoenix, AZ, USA road and highway network using vehicles instrumented with GPS-enabled onboard diagnostic devices (OBD). We demonstrate the effectiveness of our method through two scenarios and investigate the impact of changes in mobility levels on the expected CO₂ emissions associated with the experimental NTPs.     

Potential performance of urban land use and transport strategies in reducing greenhouse gas emissions: Khon Kaen case study,Thailand

ABSTRACT

Transport activities are a key contributor to greenhouse gas (GHG) emissions, global warming, and climate change. In Thailand, private cars are the second largest generator (after trucks) of GHG emissions from the transport sector. This article presents an analysis and evaluation of the implementation of land use and transport measures for reducing GHG emissions in the road network of the Khon Kaen University (KKU) area in Khon Kaen, Thailand. This research applied a bottom-up method to estimate the baseline GHG emissions for several scenarios by adopting the Clean Development Mechanism 2 (CDM2) and Pollution Control Department (PCD) methods over a 20-year planning horizon. The cleaner technology strategy clearly showed the greatest performance in reducing the GHG emission, followed by land use planning and restriction of private vehicle usage. The public transit improvement strategy illustrated the least GHG emissions reduction. Integrated scenarios clearly illustrated larger potential benefits, more effective than the individual scenarios. For both individual and integrated scenarios, the potential performances of the GHG emissions reduction estimated by the PCD method were greater than those assessed by the CDM2 method.     

TRIBUTE: Trip-based urban transportation emissions model for municipalities

This research aims at developing modeling and scenario-comparison tools to explore the impacts of various transportation and land use planning policies on changing travel behavior and eventually greenhouse gas (GHG) emissions. A Trip-Based Urban Transportation Emissions (TRIBUTE) model is developed. Data required for TRIBUTE comes from household travel surveys and emissions inventories, which is a major advantage in cases where a detailed transportation network model is unavailable. TRIBUTE is composed of two main parts: a mode choice model and an emissions forecasting model. The mode choice model is responsible for estimating modal shares of alternative modes of travel in response to changes in personal, modal, and land use attributes. The emissions forecasting model translates the modal shares into vehicle kilometers traveled, and subsequently GHG emissions. TRIBUTE is a macroscopic model intended to assist municipalities evaluate alternative transportation and land use policy scenarios and eventually select the one(s) that help them meet their future GHG emission targets. This paper reports on the conceptual framework of the developed model and presents a case study.     

Climate change and the air travel decisions of UK tourists

Whilst much effort has been made to communicate to the public the importance of reducing carbon footprints in the home, one area where emissions are growing rapidly and little attempt has been made to increase consumer understanding of the impacts is holidays, particularly those involving air travel. Using focus group research, this paper explores tourists’ awareness of the impacts of travel on climate change, examines the extent to which climate change features in holiday travel decisions and identifies some of the barriers to the adoption of less carbon-intensive tourism practices. The findings suggest that many tourists do not consider climate change when planning their holidays. The failure of tourists to engage with the climate change impact of holidays, combined with significant barriers to behavioural change, presents a considerable challenge in moving the tourism industry onto a sustainable emissions path. The findings are discussed in relation to theoretical perspectives from psychology and sociology.     

Modeling fuel saving investments and fleet management in the trucking industry: The impact of shipment performance on GHG emissions

Much has been written about the potential of technologies to reduce the greenhouse gas (GHG) emissions of trucking, but much less on the determinants of these investments. The Trucking Sector Trip Segmentation Model (TSTS) predicts how firms make these investments in the context of operating heterogeneous truck fleets to service the spatially dispersed demand of shippers. This analysis suggests that improving the performance of trucking (speeding up shipments) could reduce significantly GHG emissions: investments in technologies are incentivized by fuel savings accruing sooner. This effect could be potentially large in the US as trucking firms often discount the future heavily.     

A closer look at urban development under the emergence of autonomous vehicles: Traffic,land use and air quality impacts

Autonomous vehicles (AVs) hold great promise for increasing the capacity of existing roadways and intersections, providing more mobility to a wider range of people, and are likely to reduce vehicle crashes. However, AVs are also likely to increase travel demand which could diminish the potential for AVs to reduce congestion and cause emissions of greenhouse gases (GHG) and other air pollutants to increase. Therefore, understanding how AVs will affect travel demand is critical to understanding their potential benefits and impacts. We evaluate how adoption of AVs affects travel demand, congestion and vehicle emissions over several decades using an integrated travel demand, land-use and air quality modeling framework for the Albuquerque, New Mexico metropolitan area. We find that AVs are likely to increase demand and GHG emissions as development patterns shift to the region's periphery and trips become longer. Congestion declines along most roadways as expanded capacity from more efficient AV operation outpaces increasing demand. Most of the population can also expect a reduction in exposure to toxic vehicle emissions. Some locations will experience an increase in air pollution exposure and traffic congestion from changes in land-use and traffic patterns caused by the adoption of AVs.     

Ex-post environmental and traffic assessment of a speed reduction strategy in Madrid's inner ring-road

Since urban traffic is a major source of CO₂ and NO_x emissions, cities play a key role averting climate change and combating air pollution. Most researchers agree on the need of designing comprehensive mitigation strategies instead of applying isolated measures. Nevertheless, it is important to understand the specific impact and scope of each measure to look for the most effective synergies among them. In 2004, the Madrid City Council launched a plan to re-design its inner ring-road to move traffic out of the city centre. For safety reasons the planned speed limit for the full-renovated South-West section was finally reduced from 90 km/h to 70 km/h. Besides contributing to traffic safety, this strategy could also be seen as positive to the environment due to the associated reduced fuel consumption and lower emissions. However, lower speed limits have lower rates of community acceptance due to its impact on average travel times at the individual level. This paper conducts an ex-post evaluation of this speed reduction strategy to explore its environmental and traffic performance impacts. The results support the thesis that, in this velocity range, lower speed limits present important opportunities for reducing GHG and air pollution in the section affected by the measure, without substantially altering traffic performance. The implementation of the new speed limit policy produces a 14.4% and 16.4% reduction in CO₂ and NO_x emissions respectively, while global travel time remains virtually constant and the saturation rate decreases slightly. Besides, this cost-effective measure reveals great potential to reduce air pollution in highly populated urban areas located next to urban highways. This work provides local policy makers and city managers with useful insights regarding potential co-benefits of traffic optimization and speed reduction management to reduce mobile source emissions in urban environments.     

Opportunities in airport pavement management: Integration of BIM,the IoT and DLT

This paper aims to explore how digitalization technologies can help to better control and supervise road pavement and refurbishments at airports. In particular, Building Information Modeling, but also the Internet of Things and Distributed Ledger Technologies, have been considered. Particular attention has been devoted to the efficiency and effectiveness of management actions involving the control and supervision of maintenance and rehabilitation of runway pavement. To conduct the analysis, a use case, related to the Madrid Barajas 18R-36L runway, has been considered. Based on this case, various improvements have been detected and an operational framework has been proposed, which allows a higher level of functionality. Finally, a discussion about the capabilities and challenges for the airport industry is undertaken.     

Interplay between ethanol and electric vehicles as low carbon mobility options for passengers in the municipality of São Paulo

The Brazilian cities as well as many of the large urban centers in the world continue to expand, increasing the demand for mobility and transport, while, at the same time, the same cities are investing in greenhouse gas (GHG) mitigation to avoid climate change. Brazil's urbanization rate increased from 26% in 1940 to almost 70% in 1980. During this period, the Brazilian population tripled and the urban population multiplied by seven. In 2010, the transport sector in São Paulo accounted for 71% of the total emissions released by the energy sector. Ethanol has been considered a fuel with less greenhouse gas emissions, when compared with fossil fuels. However, ethanol production would have to double to meet the expected demand. Electric vehicles (EVs) market is expanding around the world, and is also an option to reduce the transport emissions, if powered by clean electricity. To assess whether the adoption of EVs might bring more benefits than the current ethanol, we develop prospective scenarios supported by the Long-range Energy Alternatives Planning (LEAP) simulation tool, taking a bottom-up tank-to-wheel approach to consider the CO₂ emissions of car in São Paulo. The scenario considering a substitution of 25% of gasoline-powered cars by EV in 2030 showed a reduction in energy consumption and CO₂ emissions, around 15% and 26% respectively in that year in comparison with 2015. We discuss the interplay between ethanol and EV, also considering emission coefficients from life cycle analysis conducted in Brazil, and concluded EV will have higher positive impact on climate change mitigation than ethanol.     

Bunker consumption optimization methods in shipping: A critical review and extensions

It is crucial nowadays for shipping companies to reduce bunker consumption while maintaining a certain level of shipping service in view of the high bunker price and concerned shipping emissions. After introducing the three bunker consumption optimization contexts: minimization of total operating cost, minimization of emission and collaborative mechanisms between port operators and shipping companies, this paper presents a critical and timely literature review on mathematical solution methods for bunker consumption optimization problems. Several novel bunker consumption optimization methods are subsequently proposed. The applicability, optimality, and efficiency of the existing and newly proposed methods are also analyzed. This paper provides technical guidelines and insights for researchers and practitioners dealing with the bunker consumption issues.