Environmental life cycle assessment of battery electric vehicles from the current and future energy mix perspective

Are electric vehicles really the optimal option for the transportation sector in China to approach pollution reduction and carbon neutrality goals?

Profound worldwide fleet electrification is thought to be the primary route for achieving the target of carbon neutrality. However, when and how electrification can help mitigate environmental impacts and carbon emissions in the transport sector remains unclear. Herein, the overall life-cycle environmental impacts and carbon saving range of two typical A-class vehicles in China, including electric vehicle (EV) and internal combustion engine vehicle (ICEV), were quantified by the life cycle assessment model for endpoint damage with localization parameters. The results showed that the EV outperformed the ICEV for the total environment impact after a travel distance of 39,153 km and for carbon emissions after 32,292 km. The ICEV was more carbon-friendly only when the driving distance was less than 3229 km/a. Considering a full lifespan travel distance of 150,000 km, the whole life-cycle average environmental impacts of EV and ICEV were calculated as 8.6 and 17.5 mPt/km, respectively, but the EV had 2.3 times higher impacts than the ICEV in the production phase. In addition, the EV unit carbon emission was 140 g/km, 46.8% lower than that of the ICEV. Finally, three potential reduction scenarios were considered: cleaner power mix, energy efficiency improvement and composite scenario. These scenarios contributed 19.1%, 13.0% and 32.1% reductions, respectively. However, achieving carbon peak and neutrality goals in China remains a great challenge unless fossil fuels are replaced by renewable energy. The research can provide scientific reference for the method and practice of emission reduction link identification, eco-driving choice and emission reduction path formulation.

Extending the electric vehicle battery first life: Performance beyond the current end of life threshold

Presently, Electric Vehicle batteries are considered to have reached the End of Life once their State of Health falls to 70-80%. However, this criteria is universal to all battery capacities and not based on the specific application requirements. To evaluate whether the End of Life can be extended below the current threshold, the impact of the Internal Resistance increase needs to be addressed. In this sense, this study employs a degradation aware electrothermal model to evaluate the battery performance for different use cases. The findings reveal that capacity constraints are the main cause of the End of Life, followed by power constraints. However, this is highly dependent on the battery capacity. Large capacity batteries tend to reach the End of Life for capacity constraints, whereas smaller ones show power limitations first. The temperature increase has not shown to be a restriction for any of the cases simulated. The decline in performance is for most cases (37.5% of the simulated ones) noticed below 70% State of Health, supporting that the first-life of most batteries can be extended without compromising the vehicle's performance. This is especially the case for most average drivers using large battery capacities, currently emerging on the market. The methodology proposed for the simulated cases can be extended to real time operation in the Battery Management System. Estimating the End of Life in this way can support the maximization of the first-life and only requires an appropriate use of the available data.

Assessment of building materials in the construction sector: A case study using life cycle assessment approach to achieve the circular economy

The construction sector plays a significant role in contributing to greenhouse gas (GHG) emissions, necessitating effective and practical solutions. This study addresses the underutilization of Life Cycle Assessment (LCA) in the construction sector and demonstrates its benefits as a decision-making tool for mitigating embodied carbon. The research focuses on a G+2 building in Dubai, UAE, conducting LCA during the construction phases to assess embodied carbon levels. Results indicate that the careful selection of construction materials and involvement of LCA at the early stages of construction resulted in a 26 % reduction in the building's embodied carbon. The study recognizes the limitations of LCA but emphasizes its value and recommends future research to enhance its coverage of sustainability aspects. The findings highlight the construction sector's potential to overcome anthropogenic challenges through green solutions. Policymakers' support is crucial for implementing strategies that reduce the construction industry's carbon footprint and embrace a circular economy. The study contributes to the literature by bridging the gap in understanding the application of LCA in construction decision-making. It emphasizes the importance of transitioning to sustainable practices and circularity in the construction sector. By using LCA as a tool, construction professionals can make informed choices to reduce embodied carbon. This study underscores the urgency for adopting greener practices in the construction sector, leading to a more sustainable and low-carbon future.

Prospects of recycling from end-of-life of Li-ion batteries on alleviating materials demand-supply gap in new electric vehicles in Asia

The acceptance of battery electric vehicles (BEVs) is continuously increasing to mitigate CO2 emissions, resulting in an increase in the future material demand for LIBs. Therefore, the proper handling of End-of-life (EOL) BEV batteries requires careful attention to mitigate the supply chain issues for future LIBs materials, especially in Asia. A system dynamics model assessment was performed to evaluate the EOL of LIBs by considering the dynamic lifespan, recovery rate, and economic value under three growth rate scenarios in Asia from 2022 to 2030, depending on the battery chemistry over time. We find that comparing three different scenarios to materials demand, the result showed that materials demand for LIBs is greater in higher scenarios as compared with lower and reference scenarios. Moreover, in the low scenario, the nickel demand and recovery from end-of-life LIBs BEVs will achieve 244.0 and 43.28 kt in 2030. Based on the dynamic economic evaluation, an overall, higher potential economic value of all materials would achieve around 1471 million USD in 2030 in the low scenario. This study manifested that recycling LIBs materials has enormous economic potential and would be a step towards economic sustainability, especially in Asia in the near future.

Can the new energy vehicles (NEVs) and power battery industry help China to meet the carbon neutrality goal before 2060?

China is working to boost the manufacture, market share, sales, and use of NEVs to replace fuel vehicles in transportation sector to get carbon reduction target by 2060. In this research, using Simapro life cycle assessment software and Eco-invent database, the market share, carbon footprint, and life cycle analysis of fuel vehicles, NEVs, and batteries were calculated from the last five years to next 25 years, with a focus on the sustainable development. Results indicate globally, China had 293.98 m vehicles and 45.22% worldwide highest market share, followed by Germany with 224.97 m and 42.22% shares. Annually China's NEVs production rate is 50%, and sales account for 35%, while the carbon footprint will account for 5.2 E+07 to 4.89 E+07 kgCO2e by 2021-2035. The power battery production 219.7 GWh reaches 150%-163.4%, whereas carbon footprint values in production and use stage of 1 kWh of LFP 44.0 kgCO₂eq, NCM-146.8 kgCO₂eq, and NCA-370 kgCO₂eq. The single carbon footprint of LFP is smallest at about 5.52 E+09, while NCM is highest at 1.84 E+10. Thus, using NEVs, and LFP batteries will reduce carbon emissions by 56.33%-103.14% and 56.33% or 0.64 Gt to 0.006 Gt by 2060. LCA analysis of NEVs and batteries at manufacturing and using stages quantified the environmental impact ranked from highest to lowest as ADP > AP > GWP > EP > POCP > ODP. ADP(e) and ADP(f) at manufacturing stage account for 14.7%, while other components account for 83.3% during the use stage. Conclusive findings are higher sales and use of NEVs, LFP, and reduction in coal-fired power generation from 70.92% to 50%, and increase in renewable energy sources in electricity generation expectedly will reduce carbon footprint by 31% and environmental impact on acid rain, ozone depletion, and photochemical smog. Finally, to achieve carbon neutrality in China, the NEVs industry must be supported by incentive policies, financial aid, technological improvements, and research and development. This would improve NEV's supply, demand, and environmental impact.

Global material flow analysis of end-of-life of lithium nickel manganese cobalt oxide batteries from battery electric vehicles

The global market for battery electric vehicles (BEVs) is continuously increasing which results in higher material demand for the production of Li-ion batteries (LIBs). Therefore, the end of life (EOL) of batteries must be handled properly through reusing or recycling to minimize the supply chain issues in future LIBs. This study analyses the global distribution of EOL lithium nickel manganese cobalt (NMC) oxide batteries from BEVs. The Stanford estimation model is used, assuming that the lifespan of NMC batteries follows a Weibull distribution. The global sales data of NMC batteries from 2009 to 2018 were collected and the sales data from 2019 to 2030 were estimated based on historical trends and BEV development plans in the top 10 countries for BEV sales. The result shows a view of EOL NMC batteries worldwide. In 2038, China, South Korea and the United States (US) will be the three leading countries in the recovery of NMC battery materials. An overall global flow of NMC battery materials (aluminium, copper, manganese, steel, lithium and graphite/carbon) was also predicted in this research. This study estimated the waste potential of NMC battery materials specifically in the top 10 countries and also in other countries. Finally, the economic value estimation results for recovered materials indicated that copper, aluminium and manganese will have cumulative economic values of 7.9, 4.4 and 3.9 billion US dollars in 2038, respectively. As this study considers the different specific energy of NMC batteries in the coming years due to technological advancement, the findings can provide a more realistic insight into the future demand for NMC battery materials. This study reveals that a high number of EOL NMC batteries will be accumulated in 2038 in several countries. Therefore, large-scale recycling infrastructures should be set up to improve the efficiency of the recovery of battery materials.

Impact assessment of crude oil mix, electricity generation mix, and vehicle technology on road freight emission reduction in China

To achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China's version of the GREET model was established to evaluate the impact of crude oil mix, electricity mix, and vehicle technology on China's reduction in road freight emissions. The results show that the import share of China's crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China's coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), by approximately 6.5% in 2020 compared to 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potentials for energy-saving and emission reduction at various stages of the fuel life cycle are different. In addition, in a comparative study of vehicle technology, the results show that (1) for medium-duty trucks (MDTs) and heavy-duty trucks (HDTs), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty trucks (LDTs), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.

Life Cycle Prediction Assessment of Battery Electrical Vehicles with Special Focus on Different Lithium-Ion Power Batteries in China

The incentive policies of new energy vehicles substantially promoted the development of the electrical vehicles technology and industry in China. However, the environmental impact of the key technology parameters progress on the battery electrical vehicles (BEV) is uncertain, and the BEV matching different lithium-ion power batteries shows different environmental burdens. This study conducts a life cycle assessment (LCA) of a BEV matching four different power batteries of lithium-ion phosphate (LFP), lithium-ion nickel-cobalt-manganese (NCM), lithium manganese oxide (LMO), and lithium titanate oxide (LTO) batteries. In addition, the 2025 and 2030 prediction analyses of the batteries production and life cycle BEV are conducted with the specially considered change and progress of the power battery energy density, battery manufacturing energy consumption, electricity structure, battery charge efficiency, and vehicle lightweight level. In addition, sensitivity analyses of power battery energy density, battery manufacturing energy consumption, electricity structure, and battery charge efficiency are conducted. The results show that the LFP battery is more environmentally friendly in the global warming potential (GWP) and acidification potential (AP), and the NCM battery is more environmentally friendly in abiotic depletion (fossil) (ADP(f)) and human toxicity potential (HTP). However, the LTO battery shows the highest environmental impact among the four environmental impact categories due to the lower energy density. For life cycle BEV, GWP and ADP(f) of BEV based on LFP, NCM, and LMO are lower than those of internal combustion engine vehicles (ICEV), while AP and HTP of BEV based on the four batteries are higher than those of ICEV. The grave-to-cradle (GTC) phase of vehicle has substantial environmental benefit to reduce the human toxicity emission. With the improvement of the battery density, battery charge efficiency, electricity structure, and glider lightweight level, life cycle BEVs based on the four different batteries show substantial environmental benefits for four environmental impact categories.

Regional Differences and Spatial Convergence of Green Development in China

Green development is an important path to achieving economic, environmental, and social sustainability. Based on the comprehensive evaluation system of economy, environment, and society, this study used the entropy method, Theil index decomposition method, and spatial β-convergence model to study the differences and spatial convergence of China’s green development from 2010 to 2020. The research conclusions are as follows: First, China’s green development has an upward trend, and the eastern region is higher. Second, the regional differences in green development have the characteristic of rising first and then falling, and the differences within regions are the main source of imbalances in China’s green development. Third, China’s green development has obvious characteristics of spatial absolute β-convergence and spatial conditional β-convergence. Green innovation is conducive to narrowing the gaps in the convergence speed of regional green development. The research results comprehensively explain the characteristics of China’s green development and provide realistic evidence for China’s green development in the future.

Estimation of Greenhouse Gas Emissions of Petrol, Biodiesel and Battery Electric Vehicles in Malaysia Based on Life Cycle Approach

A steady rise in the ownership of vehicles in Malaysia has drawn attention to the need for more effective strategies to reduce the emissions of the road transport sector. Although the electrification of vehicles and replacing petrol with biofuel are the strategies being considered in Malaysia, these strategies have yet to be fully evaluated from an environmental perspective. In this study, a life cycle assessment was conducted to compare the greenhouse gas emissions of different types of transportation means (passenger cars, two-wheelers (motorbikes), and buses) with several types of powertrains (petrol, biodiesel, electricity) based on multiple lifecycle stages in Malaysia. The impact of considering land use change for the biodiesel production in the LCA was also considered in this study. It was found that the transition from internal combustion engine vehicles fueled by petrol to electric vehicles would reduce the greenhouse gas emission for passenger cars, two-wheelers, and buses. However, because the greenhouse gas emissions of biodiesel-fueled vehicles are higher than those of petrol-fueled vehicles, even without considering land use change, the results indicate that the transition from a 10% to 20% biofuel blend, which is a current strategy in Malaysia, will not result in a reduction in greenhouse gas emissions for the transport sector in Malaysia.

A Review of EV Battery Utilization in Demand Response Considering Battery Degradation in Non-Residential Vehicle-to-Grid Scenarios

Integrating fleets of electric vehicles (EVs) into industrial applications with smart grids is an emerging field of important research. It is necessary to get a comprehensive overview of current approaches and proposed solutions regarding EVs with vehicle-to-grid and smart charging. In this paper, various approaches to battery modeling and demand response (DR) of EV charging in different decentralized optimization scenarios are reviewed. Modeling parameters of EVs and battery degradation models are summarized and discussed. Finally, optimization approaches to simulate and optimize demand response, taking into account battery degradation, are investigated to examine the feasibility of adapting the charging process, which may bring economic and environmental benefits and help to alleviate the increasing demand for flexibility. There is a lack of studies that comprehensively consider battery degradation for EV fleets in DR charging scenarios where corresponding financial compensation for the EV owners is considered. Therefore, models are required for estimating the level of battery degradation endured when EVs are utilized for DR. The level of degradation should be offset by providing the EV owner with subsidized or free electricity provided by the company which is partaking in the DR. This trade-off should be optimized in such a manner that the company makes cost savings while the EV owners are compensated to a level that is at least commensurate with the level of battery degradation. Additionally, there is a lack of studies that have examined DR in smart grids considering larger EV fleets and battery degradation in multi-criteria approaches to provide economic and environmental benefits.

Optimal Management for EV Charging Stations: A Win–Win Strategy for Different Stakeholders Using Constrained Deep Q-Learning

Given the additional awareness of the increasing energy demand and gas emissions’ effects, the decarbonization of the transportation sector is of great significance. In particular, the adoption of electric vehicles (EVs) seems a promising option, under the condition that public charging infrastructure is available. However, devising a pricing and scheduling strategy for public EV charging stations is a non-trivial albeit important task. The reason is that a sub-optimal decision could lead to high waiting times or extreme changes to the power load profile. In addition, in the context of the problem of optimal pricing and scheduling for EV charging stations, the interests of different stakeholders ought to be taken into account (such as those of the station owner and the EV owners). This work proposes a deep reinforcement learning-based (DRL) agent that can optimize pricing and charging control in a public EV charging station under a real-time varying electricity price. The primary goal is to maximize the station’s profits while simultaneously ensuring that the customers’ charging demands are also satisfied. Moreover, the DRL approach is data-driven; it can operate under uncertainties without requiring explicit models of the environment. Variants of scheduling and DRL training algorithms from the literature are also proposed to ensure that both the conflicting objectives are achieved. Experimental results validate the effectiveness of the proposed approach.

Forecast of Electric Vehicle Sales in the World and China Based on PCA-GRNN

Since electric vehicles (EVs) could reduce the growing concerns on environmental pollution issues and relieve the social dependency of fossil fuels, the EVs market is fast increased in recent years. However, a large growth in the number of EVs will bring a great challenge to the present traffic system; thus, an acceptable model is necessary to forecast the sales of EVs in order to better plan the appropriate supply of necessary facilities (e.g., charging stations and sockets in car parks) as well as the electricity required on the road. In this study, we propose a model to predict the sales volume and increase rate of EVs in the world and China, using both statistics and machine learning methods by combining principle component analysis and a general regression neural network, based on the previous 11 years of sales data of EVs. The results indicate that a continuing growth in the sales of EVs will appear in both the world and China in the coming eight years, but the sales increase rate is slowly and continuously deceasing because of the persistent growth of the basic sales volume. The results also indicate that the increase rate of sales of EVs in China is higher than that of the world, and the proportion of sales of EVs in China will increase gradually and will be above 50% in 2025. In this case, large accessory facilities for EVs are required in China in the coming few years.

Assessing the Energy Consumption and Driving Range of the QUIET Project Demonstrator Vehicle

This article summarises the experimental testing campaign performed at the Joint Research Centre (JRC) on the demonstrator battery electric vehicle (BEV) of the European Union Horizon 2020 research project QUIET. The project, launched in October 2017, aimed at developing an improved and energy-efficient electric vehicle with increased driving range under real-world driving conditions, focusing on three areas: improved energy management, lightweight materials with enhanced thermal insulation properties, and improved safety and comfort. A heating, venting, and air conditioning (HVAC) system based on the refrigerant R290 (propane), a phase change material (PCM) thermal storage system, infrared heating panels in the near field of the passengers, lightweight materials for seat internal structures, and composite vehicle doors with a novel atomically precise manufacturing (APM) aluminium foam are all the breakthrough technologies installed on the QUIET demonstrator vehicle. All these innovative technologies allow the energetic request for cooling and heating the cabin of the demonstrator vehicle under different driving conditions and the weight of the vehicle components (e.g., doors, windshields, seats, heating, and air conditioning) to be reduced by about 28%, leading to an approximately 26% driving range increase under both hot (40 °C) and cold (−10 °C) weather conditions.

Life Cycle Assessment of Battery Electric and Internal Combustion Engine Vehicles Considering the Impact of Electricity Generation Mix: A Case Study in China

Battery Electric Vehicles (BEVs) are considered to have higher energy efficiency and advantages to better control CO2 emissions compared to Internal Combustion Engine Vehicles (ICEVs). However, in the context that a large amount of thermal power is still used in developing countries, the CO2 emission reduction effectiveness of BEVs can be weakened or even counterproductive. To reveal the impact of the electricity generation mix on carbon emissions from vehicles, this paper compares the life cycle carbon emissions of BEVs with ICEVs considering the regional disparity of electricity generation mix in China. According to Life Cycle Assessment (LCA) analysis and regional electricity carbon intensity, this study demonstrates that BEVs in the region with high penetration of thermal power produce more CO2 emissions, while BEVs in the region with higher penetration of renewable energy have better environmental performance in carbon emission reduction. For instance, in the region with over 50%penetration of renewable energy, a BEV can reduce more CO2 (18.32 t) compared to an ICEV. Therefore, the regions with high carbon emissions from vehicles need to increase the proportion of renewable generation as a priority rather than promoting BEVs.