Search Results (11)

The efficiency of the same vehicle can vary in different regions, posing unique challenges and implications for electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) within a country. However, most studies have regarded countries as single entities, and it is difficult to assess differences in efficiency between similar entities by simply using the life cycle analysis (LCA) method. To provide the specific environmental efficiency of vehicles in each region, in this study, we used data from 100 cities in 30 provinces in China (4 provinces are not discussed due to a lack of data) and constructed a new road congestion indicator that simulated different road conditions at different times and in different regions. A more effective method, which consisted of LCA, two-stage data envelopment analysis (DEA) and a slack-based model (SBM), was integrated to reflect the phases of LCA more clearly. The results show that the well-to-wheel (WTW) emission range of internal combustion engine vehicles (ICEVs) is 288.28–217.40 CO₂-eq g/km, while it is 248.20–26.67 CO₂-eq g/km for EVs, which means the WTW carbon emissions of EVs are generally lower than those of ICEVs (except in Heilongjiang Province). Furthermore, it was concluded that provinces with a high proportion of hydropower and a high degree of power autonomy could adjust the proportion of thermal power and inter-provincial power transmission to enhance environmental sustainability, and this would not change provincial environmental efficiency. The analysis suggests that provinces should consider both environmental protection and electricity sustainability when planning their own power development, rather than only focusing on improving environmental efficiency. Full article

In light of carbon peak and carbon neutrality goals, China has attached great importance to energy savings and carbon reduction. Carbon reduction in the transport sector is critical to achieving the two-carbon target, as it accounts for 9.41% of total carbon emissions. As the sharing economy grows, car sharing is considered to present excellent carbon reduction potential in the transportation sector. However, the current research is focused on car sharing usage, with a lack of research on the carbon reduction capability of car sharing in China. Hence, this study aims to investigate the carbon reduction capacity of car sharing, including usage rates of car-share services and changes in travel behavior, through an online questionnaire combined with carbon emission data from the transportation sector. The study aims to analyze the contribution of car-share services to carbon reduction in the transportation sector under the current model. The well-to-wheel (WTW) approach is employed, including the energy consumption of vehicles and carbon emissions in the production process. The research results indicate that the introduction of car-sharing services increases driving energy consumption; however, this increase is offset by the decrease in carbon emissions as a result of the production process. Therefore, the overall effect is a reduction in carbon emissions of 1.058971 million tons in 2021, accounting for 1.95 percent of total transport carbon emissions. In addition, the impact on different modes on carbon emission reduction is also explored in this study. The results demonstrate that the private car disposal rate shows the most significant influence on traffic carbon emissions; a 10% reduction in the number of private cars can lead to a 2.48% carbon reduction. The relevant conclusions of this study can provide support for the future development of car sharing in China and the reduction of carbon emissions in the transportation sector. Full article

Global energy and environmental issues are becoming increasingly serious, and the promotion of clean energy and green transportation has become a common goal for all countries. In the logistics industry, traditional fuels such as diesel and natural gas can no longer meet the requirements of energy and climate change. Hydrogen fuel cell logistics vehicles are expected to become the mainstream vehicles for future logistics because of their “zero carbon” advantages. The GREET model is computer simulation software developed by the Argonne National Laboratory in the USA. It is extensively utilized in research pertaining to the energy and environmental impact of vehicles. This research study examines four types of logistics vehicles: hydrogen fuel cell vehicles (FCVs), electric vehicles, LNG-fueled vehicles, and diesel-fueled vehicles. Diesel-fueled logistics vehicles are currently the most abundant type of vehicle in the logistics sector. LNG-fueled logistics vehicles are considered as a short-term alternative to diesel logistics vehicles, while electric logistics vehicles are among the most popular types of new-energy vehicles currently. We analyze and compare their well-to-wheels (WTW) energy consumption and emissions with the help of GREET software and conduct lifecycle assessments (LCAs) of the four types of vehicles to analyze their energy and environmental benefits. When comparing the energy consumption of the four vehicle types, electric logistics vehicles (EVs) have the lowest energy consumption, with slightly lower energy consumption than FCVs. When comparing the nine airborne pollutant emissions of the four vehicle types, the emissions of the FCVs are significantly lower than those of spark-ignition internal combustion engine logistics vehicles (SI ICEVs), compression-ignition direct-injection internal combustion engine logistics vehicles (CIDI ICEVs), and EVs. This study fills a research gap regarding the energy consumption and environmental impact of logistics vehicles in China. Full article

The purpose of this paper is to discover the impacts of contradictory factors in the application of agricultural residue with sustainable biofuel benefits. Based on the Life cycle assessment (LCA) approach, the quantitative LCA assessment model and approach have been established, coupling upstream cultivation and downstream jet biofuel product, which would benefit agriculture residue choice. The LCA model investigated the effects of interaction factors on energy consumption, including land release and agriculture residue use change. The computational framework of the LCA model is classified into three sub-models, including the cultivation and harvesting model, the refining process and distribution model, and the flight model. According to uncertainty analysis by the LCA model, the positive energy gains have been conducted at a wide range of hydrogen production and methanol production. The application model is represented by six types of typical aircraft widely used in China, including the LTO cycle module, actual cruising distance and maximum cruising distance module, actual payload, and maximum payload module. In the whole life cycle assessment, GHGs of agriculture residue is 17.9 gCO₂e/MJ while petroleum-based jet fuel is 90.2 gCO₂e/MJ. The order of GHGs in WTW (well to wheel) is agriculture residue < corn stover < beanstalk < wheat straw < rice straw. The land release conducted obviously to the total GHGs emission for rice straw, which indicated that land release should involve in the LCA. Full article

In recent years, growing awareness about environmental issues is pushing humankind to explore innovative technologies to reduce the anthropogenic sources of pollutants. Among these sources, internal combustion engines in non-road mobile machinery (NRMM), such as agricultural tractors, are one of the most important. The aim of this work is to explore the possibility of replacing the conventional diesel engine with an electric powertrain powered by a hybrid storage system, consisting of a small battery pack and a fuel-cell system. The battery pack (BP) is necessary to help the fuel cell manage sudden peaks in power demands. Numerical models of the conventional powertrain and a fuel-cell tractor were carried out. To compare the two powertrains, work cycles derived from data collected during real operative conditions were exploited and simulated. For the fuel-cell tractor, a control strategy to split the electric power between the battery pack and the fuel cell was explored. The powertrains were compared in terms of greenhouse gas emissions (GHG) according to well-to-wheel (WTW) equivalent ${\mathrm{CO}}_2$ emission factors available in the literature. Considering the actual state-of-the-art hydrogen production methods, the simulation results showed that the fuel-cell/battery powertrain was able to accomplish the tasks with a reduction of about 50% of the equivalent ${\mathrm{CO}}_2$ emissions compared to traditional diesel-powered vehicles. Full article

The freight sector is expected to keep, or even increase, its fundamental role for the major modern economies, and therefore actions to limit the growing pressure on the environment are urgent. The use of electricity is a major option for the decarbonization of transports; in the heavy-duty segment, it can be implemented in different ways: besides full electric-battery powertrains, electricity can be used to supply catenary roads, or can be chemically stored in liquid or gaseous fuels (e-fuels). While the current EU legislation adopts a tailpipe Tank-To-Wheels approach, which results in zero emissions for all direct uses of electricity, a Well-To-Wheels (WTW) method would allow accounting for the potential benefits of using sustainable fuels such as e-fuels. In this article, we have performed a WTW-based comparison and modelling of the options for using electricity to supply heavy-duty vehicles: e-fuels, eLNG, eDiesel, and liquid Hydrogen. Results showed that the direct use of electricity can provide high Greenhouse Gas (GHG) savings, and also in the case of the e-fuels when low-carbon-intensity electricity is used for their production. While most studies exclusively focus on absolute GHG savings potential, considerations of the need for new infrastructures, and the technological maturity of some options, are fundamental to compare the different technologies. In this paper, an assessment of such technological and non-technological barriers has been conducted, in order to compare alternative pathways for the heavy-duty sector. Among the available options, the flexibility of using drop-in, energy-dense liquid fuels represents a clear and substantial immediate advantage for decarbonization. Additionally, the novel approach adopted in this paper allows us to quantify the potential benefits of using e-fuels as chemical storage able to accumulate electricity from the production peaks of variable renewable energies, which would otherwise be wasted due to grid limitations. Full article

New energy vehicles (NEVs), especially electric vehicles (EVs), address the important task of reducing the greenhouse effect. It is particularly important to measure the environmental efficiency of new energy vehicles, and the life cycle analysis (LCA) model provides a comprehensive evaluation method of environmental efficiency. To provide researchers with knowledge regarding the research trends of LCA in NEVs, a total of 282 related studies were counted from the Web of Science database and analyzed regarding their research contents, research preferences, and research trends. The conclusion drawn from this research is that the stages of energy resource extraction and collection, carrier production and energy transportation, maintenance, and replacement are not considered to be research links. The stages of material, equipment, and car transportation and operation equipment settling, and forms of use need to be considered in future research. Hydrogen fuel cell electric vehicles (HFCEVs), vehicle type classification, the water footprint, battery recovery and reuse, and battery aging are the focus of further research, and comprehensive evaluation combined with more evaluation methods is the direction needed for the optimization of LCA. According to the results of this study regarding EV and hybrid power vehicles (including plug-in hybrid electric vehicles (PHEV), fuel-cell electric vehicles (FCEV), hybrid electric vehicles (HEV), and extended range electric vehicles (EREV)), well-to-wheel (WTW) average carbon dioxide (CO₂) emissions have been less than those in the same period of gasoline internal combustion engine vehicles (GICEV). However, EV and hybrid electric vehicle production CO₂ emissions have been greater than those during the same period of GICEV and the total CO₂ emissions of EV have been less than during the same period of GICEV. Full article

In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks. Full article

Several countries have set ambitious targets for the transport sector that mandate a gradual increase in advanced biofuel content in the coming years. The current work addresses this transition and indicates two promising gasoline bio-blendstocks: Anisole and isobutanol. The whole value chains of these bio-components were considered, focusing on end-use performance, but also analyzing feedstock and its conversion, well-to wheel (WTW) greenhouse gas (GHG) emissions and costs. Three alternative fuels, namely a ternary blend (15% anisole, 15% isobutanol, 70% fossil gasoline on an energy basis) and two binary blends (15% anisole with fossil gasoline and 30% isobutanol with fossil gasoline), were tested, focusing on their drop-in applicability in spark ignition (SI) engines. The formulated liquid fuels performed well and showed the potential to increase brake thermal efficiency (BTE) by 1.4% on average. Measured unburned hydrocarbons (HC) and carbon monoxide (CO) emissions were increased on average by 12–29% and 17–51%, respectively. However, HC and CO concentrations and exhaust temperatures were at acceptable levels for proper catalyst operation. The studied blends were estimated to bring 11–22% of WTW GHG emission reductions compared to base gasoline. Additionally, the fleet performance and benefits of flexi-fuel vehicles (FFV) were modeled for ternary blends. Full article

Recent research has investigated the energy saving potential of regenerative suspension. However, the greenhouse gas (GHG) emission mitigation potential of regenerative suspension in battery electric vehicles (BEVs) has not been considered. Life cycle assessment (LCA) is a typical method for evaluating GHG emissions but is rarely used in vehicle control design. Here we explore the effects of regenerative suspension on reducing the GHG emissions from a BEV, whose control design considers well-to-wheels (WTW) analysis. The work first conducts the WTW analysis and modelling of the GHG emissions from a BEV equipped with regenerative suspension. Based on the models, the relation between suspension control parameters and GHG emissions is obtained. To reach a compromise between dynamic performance and environmental benefit, two types of control parameters are recommended and their switch rules during the operation are proposed. Finally, we take a case study with different driving cycles, road levels and country contexts. The results show that considering WTW analysis in control design can contribute to GHG emission mitigation, especially for countries that have a high-carbon intensity of the electricity grid. These findings provide a quantitative reference for technology path decision on regenerative suspension. This paper may provide a new insight for employing LCA in vehicle design. Full article

This study, using Chongqing City of China as an example, predicts the future motor vehicle population using the Gompertz Model and the motorcycle population using the piecewise regression model, and predicts and analyzes fuel consumption and greenhouse gas (GHG) emissions of motor vehicles from 2016 to 2035 based on the bottom-up method under different scenarios of improving the fuel economy of conventional vehicles, promoting alternative fuel vehicles, and the mixed policy of the above two policy options. The results indicate that the total population of motor vehicles in Chongqing will increase from 4.61 million in 2015 to 10.15 million in 2035. In the business-as-usual scenario, the road-transportation energy demand in Chongqing will keep increasing from 2015 and will peak in 2030, before it begins to decline by 2035. The trends for the tank to wheel (TTW) and well to wheel (WTW) GHG emissions are similar to that of energy demand. The WTW GHG emissions will increase from 24.9 Mt CO₂e in 2016 to 50.5 Mt CO₂e in 2030 and will then gradually decline to 48.9 Mt CO₂e in 2035. Under the policy scenarios of improving fuel economy of conventional fuel passenger cars, promoting alternative fuel vehicles, and their mixed policy, direct energy consumption and TTW and WTW GHG emissions from 2016 to 2035 will be reduced to different levels. It is also found that the two types of policies have a hedging effect on the direct energy-consumption saving, TTW, and WTW GHG emission reductions. Sensitivity analysis of key parameters and policy settings is conducted to investigate the impact of their changes on the vehicle population projection, direct energy demand, and WTW GHG emissions. Some policy implications are suggested to provide reference for the formulation and adjustment of Chongqing’s, or even China’s, low-carbon road transportation policies in the future based on the analysis results. Full article