Vehicle Stock Research Articles

Anticipatory climate policy mix pathways: a framework for ex-ante construction and assessment applied to the road transport sector

ABSTRACT Globally, climate policy implementation is failing to deliver on the ambitions outlined in the Paris Agreement and countries’ Nationally Determined Contributions. We argue that a more strategic and anticipatory approach to policy mix design and implementation can help contribute to realizing these ambitions. Policy mixes need to co-evolve as energy transitions progress, in order to effectively target multiple transition challenges as these change over time. Accordingly, policy assessments need to both consider interactions between instruments and adopt a dynamic perspective, in terms of design logics and evaluative criteria. We highlight the need for a construction and assessment methodology for designing policy mix pathways which explicitly considers durability risks which could weaken support and lead to dismantling, and anticipatory design principles which can help mitigate these risks. Our paper addresses this gap by proposing and illustrating a novel framework for policy instrument mix pathway construction and ex-ante assessment. We identify generalizable durability challenges for effective anticipatory design: dynamic cost effectiveness, the distributive impacts and acceptance of pathways, along with fiscal and governance requirements for effective implementation. We demonstrate the value of the approach by application to the German light-duty vehicle sector transition. We construct and comparatively assess three illustrative pathways promising to deliver the German LDV sector 2030 GHG targets. The pathways differ in logic, and which of three main market dynamics driving a diffusion-stage transition they emphasize: battery electric vehicle (BEV) purchase, vehicle stock usage, and internal combustion engine (ICE) vehicle scrappage. Accordingly, the pathways utilize different instrument combinations, design features and calibrations. We also assess the illustrative pathways and discuss trade-offs. We argue that this approach can help improve climate policy planning and implementation processes, and increase the likelihood attaining ambitious mitigation targets.

Scenario analysis of waste tires from China's vehicles future

As a byproduct of vehicles, tires are utilized in large quantities with the widespread promotion of vehicles. Long-term accumulation of non-degradable waste tires occupies land resources and poses severe environmental threats. Projecting future waste tire volumes provides a scientific basis for preventing excessive accumulation, enables proactive planning of recycling strategies, reduces environmental pollution and promotes waste tire recycling. Using a bottom-up Road Transport Waste Tire Stock model, this study projects vehicle stocks and corresponding annual increases in waste tires from 2002 to 2050. The study reveals that China's vehicle and waste tire stock follows an S-curve growth. Vehicle ownership is projected to increase from 276 million in 2020 to 490–583 million by 2050. Between 2002 and 2030, waste tire generation from vehicles is expected to rise from 4.79 million tons to 18.13–18.57 million tons. By 2050, growth will slow, but the total output will still reach 18.90–19.85 million tons, with cargo trucks contributing 68%. By 2050, Shandong is the leading province in waste tire production, generating 1.82 million tons annually, accounting for 9.1%. Hainan will see the highest growth rate by 2030, with a 40% increase from 2020 levels. The study, based on current policies, presents three recommendations: improving waste tire tracking and recycling systems, implementing region-specific management strategies, and promoting the resource recovery of raw materials from cargo trucks waste tires. These measures aim to enhance waste tire management and foster rubber resource recycling.

Modeling fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles in 1970–2020

Abstract. Vehicles are among the most important contributors to global anthropogenic CO2 emissions. However, the lack of fuel-, vehicle-type-, and age-specific information about global on-road CO2 emissions in existing datasets, which are available only at the sector level, makes these datasets insufficient for supporting the establishment of emission mitigation strategies. Thus, a fleet turnover model is developed in this study, and CO2 emissions from global on-road vehicles from 1970 to 2020 are estimated for each country. Here, we analyze the evolution of the global vehicle stock over 50 years, identify the dominant emission contributors by vehicle and fuel type, and further characterize the age distribution of on-road CO2 emissions. We find that trucks accounted for less than 5 % of global vehicle ownership but represented more than 20 % of on-road CO2 emissions in 2020. The contribution of diesel vehicles to global on-road CO2 emissions doubled during the 1970–2020 period, driven by the shift in the fuel-type distribution of vehicle ownership. The proportion of CO2 emissions from vehicles in developing countries such as China and India in terms of global emissions from newly registered vehicles significantly increased after 2000, but global CO2 emissions from vehicles that had survived more than 15 years in 2020 still originated mainly from developed countries such as the United States and countries in the European Union. The data are publicly available at https://doi.org/10.6084/m9.figshare.24548008 (Yan et al., 2024).

Sustainable Wheels of Fortune: Understanding the Asymmetric Bond between Green Finance and Electric Vehicle Adoption

Over the past few years, there has been a growing convergence of energy and environmental challenges globally, necessitating decisive actions. In response to these imperatives, countries have embraced electric vehicles as a transformative solution. This study probes the connection between green finance and electric-vehicle adoption in the top 10 economies with the greatest stock of electric vehicles. Previous investigations employing panel-data tools established consistent findings about the green-finance/electric-vehicle nexus. However, some countries exhibit distinct relationships. Using the quantile-on-quantile methodology, we analyze the time-series interdependence within individual countries, providing insights into the variables’ asymmetric association. The findings show that green finance positively influences the electric-vehicle stock in certain economies, specifically at distinct points within the data distribution, each characterized by its unique traits. The findings emphasize the significance of green finance measures in promoting widespread electric-vehicle adoption, contributing to environmental sustainability, and fostering a shift toward low carbon consumption.

Prediction of Market Share of Different Vehicle Powertrains on Interprovincial Highways amid the Development of Urban Agglomerations

In the coordinated development of urban agglomerations in China, inter-city connections within urban agglomerations have been gradually strengthened, with more interprovincial highways built. Given the complex geological conditions, interprovincial highways often require tunnels. The construction of tunnel ventilation facilities needs to take into account the types of vehicle, traffic flows, and the market share of different vehicle powertrains using the highways. This paper aims to develop a method to predict the future market share of the powertrains of different types of vehicle on the interprovincial highway. The paper builds a policy cluster by analyzing the regional policies for new energy vehicles and then builds a parameter cluster by summarizing industry reports, expert opinion, and policy clusters to predict the market share of different vehicle types categorized by powertrains. Finally, based on the historical vehicle stock data, and using vehicle sales and scrappage rate models, the paper builds a future stock cluster to estimate the annual stock share of different vehicle powertrains up to 2045. The paper applies the method to the interprovincial highway S7 in the Yangtze River Delta urban agglomeration. It obtains the future trend of the market share of the powertrains of different vehicle types on S7 in the target year, validating the model. The results show that the share of new energy vehicles on the S7 highway will increase gradually until 2025. Electric vehicles will dominate the growth, with light trucks forming the highest proportion, followed by cars, and finally buses and heavy trucks.

Research on volatility spillover effects between traditional energy market and China's new energy vehicle stock market

Research on volatility spillover effects between traditional energy market and China's new energy vehicle stock market

Vehicle Stock Numbers and Survival Functions for On-Road Exhaust Emissions Analysis in India: 1993–2018

Road transport plays a crucial role in sustaining all the personal and freight movement needs of residential, commercial, and industrial activities, and in Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads contribute to as much as 50% of particulate matter pollution in a year. Therefore, effective management of vehicle exhaust emissions is vital not only for improving current air quality but also for ensuring the long-term benefits from efforts to reduce air pollution. In the approved clean air action plans for 131 cities under the national clean air program (NCAP), more than 50% of the implementable actions are transport-centric. Having a reliable and replicable vehicle exhaust emissions inventory is essential for effective planning, which can help establish a baseline, support scenario analysis, and allow for tracking progress in the sector. This process begins with accessing accurate vehicle stock numbers, typically obtained from vehicle registration databases, traffic surveys, and other governmental records. Often, in low- and middle-income countries like India, these numbers require extensive data cleaning before they can be used for emissions and pollution analysis. This paper presents a cleaned, open-access vehicle stock database for India and outlines a methodology to build and maintain an in-use vehicle age-mix database for future years. The database covers the years 1993 to 2018 for the entire country and individual states, along with estimates of the age distribution of vehicles using survival functions. By offering a comprehensive and reliable data source, this paper aims to support sustainable national and urban air quality management efforts, helping policymakers and stakeholders make informed decisions to improve air quality and public health.

Application of Machine Learning in Stock Market Return Forecasting

With the development of our country's financial market, people pay more attention to the stock market return forecast, which can bring the investors a lot of income and also become a tool of risk management. Machine learning (ML) and artificial intelligence (AI) are becoming increasingly sophisticated and have achieved amazing results in many fields. Machine learning and deep learning algorithm models can process huge amounts of data, from which they can quickly process and analyze laws, many scholars try to apply various machine learning models to the financial field. This paper first expounds the theoretical basis of stock market return prediction, and summarizes the main literature in this field in recent years, from the traditional stock prediction model to the machine learning prediction model. Finally, the traditional stock prediction model ARIMA model and the deep learning LSTM neural network model are selected for comparative empirical research. The sample data are from the Tushare big data community, taking the new energy vehicle stock BYD (002594) as an example. The empirical results show that the prediction accuracy and stability of LSTM neural network are far higher than ARIMA model, and it will have broad application prospects in financial prediction and other fields in the future.

Economic impact of ACES trends on the automotive value chain: a forecast exploratory study of the Chinese automotive industry in 2030

In the context of green transportation, the automotive industry is undergoing a revolution in autonomous, connected, electric, and shared (ACES) vehicles. ACES vehicles have a relatively short history and there is limited relevant market data available. Therefore, quantitative research on the economic impact of ACES trends remains a new area of exploration. The purpose of the paper is to explore the economic impact of ACES trends on the automotive value chain, with a specific focus on the production and aftermarket segments. In the paper, a detailed quantitative analysis of the installation scale and the market size of Chinese automotive production as well as the income changes of Chinese automotive aftermarket in 2030 is conducted. The findings show that the new markets for power batteries, electric powertrains, sensors, in-vehicle software and chips are created, thereby delivering more value to the business. While the ACES trends are expected to decrease the average aftermarket income per vehicle, the growth of the vehicle stock suggests significant potential for the development of the automotive aftermarket in 2030. Our research contributes by offering a business perspective on the impact of ACES trends. The quantitative insights presented are timely and crucial for all the stakeholders along the value chain, enabling them to adapt and thrive in the dynamic automotive landscape and align their strategies with the transformative ACES trends.

Towards Sustainable Mobility: Assessing the Benefits and Implications of Internal Combustion Engine Vehicle Bans and Battery Electric Vehicle Uptake in Qatar

The global shift towards sustainable transportation, primarily through vehicle electrification, is critical in addressing climate change. Qatar presents a knowledge gap with specific challenges and opportunities in this transition. This study calculates the potential reduction in CO2-eq, NOx, and PM2.5 emissions resulting from substituting Internal Combustion Engine Vehicles (ICEVs) with Battery Electric Vehicles (BEVs) in Qatar, considering ICEV ban scenarios in 2030, 2035, and 2040, alongside five policy pathways. A Vehicle Stock Model (VSM) simulates Qatar’s fleet evolution from 2022 to 2050, focusing on the vehicle’s operational phase. An ICEV ban in 2030 would result in a 34% cumulative emission reduction in road transport between 2022 and 2050 compared with the Business-as-Usual (BAU) scenario. For NOx and PM2.5, cumulative emissions for the 2030 ICEV ban pathways are approximately 20% and 9% lower, respectively, compared with BAU. This study underscores the necessity of localising environmental strategies to meet Qatar’s specific needs and climate commitments, where results indicate significant emission reductions are possible through BEVs.

Urbanization inequality: evidence from vehicle ownership in Chinese cities

Unequal outcomes resulting from urbanization can pose a significant challenge to sustainable development. Vehicles are an important urbanization dimension as a critical component of urban infrastructure by providing mobility and accessibility to social services. China’s vehicle ownership (referred to as in-use vehicle stocks) has been growing quickly since 2000, but its per capita stocks are still much lower than that in developed economies. This raises the question of whether and when China’s vehicle stocks will reach a peak level close to that in the developed countries. By analyzing vehicle stocks in 283 Chinese cities during 2001–2018, we have the following findings: (1) vehicle stocks are predominantly distributed in northern and eastern coastal cities and provincial capital cities; (2) inequality in vehicle ownership rates between cities shows a declining trend at both national and region scales; (3) the growth of vehicle ownership rates follows an S-shape curve and most cities are still at the early stage of motorization; (4) China is likely to have a lower saturation level of vehicle ownership rate. These results could help to accurately forecast future vehicle demand in China, estimate the resulting environmental impacts, and explore strategies to achieve carbon neutrality in transportation.

Financing the future: Asymmetric association between green investment and electric vehicles

Green investment in electric vehicles represents a pivotal shift towards a sustainable future, promising to revolutionize our transportation systems while significantly reducing greenhouse gas emissions. This research aims to probe the linkage between green investment and electric vehicles across the top 10 economies with the highest electric vehicle adoption rates (China, USA, Norway, Germany, UK, France, Portugal, Netherlands, Belgium, and South Korea). Unlike earlier studies that primarily utilized panel data methods and overlooked the individual nuances of each country, our investigation employs the advanced ‘Quantile-on-Quantile’ technique. This novel approach enables us to delve into the relationships between variables within each specific country, thereby improving the precision of our analysis. As a result, this study provides a comprehensive global viewpoint, revealing nuanced findings about each nation's distinct characteristics. The study's findings express a positive connection between green investment and the electric vehicle stock in various segments of the sample economies. Furthermore, this research highlights diverse trends in these connections within different nations. The results emphasize policymakers’ need to conduct comprehensive evaluations and develop effective strategies to address changes in both green investment and electric vehicles.

Impact of lightweight materials substitution on material stock and carbon emission of private vehicles in China

Impact of lightweight materials substitution on material stock and carbon emission of private vehicles in China

Exploring the Cross-Correlations between Tesla Stock Price, New Energy Vehicles and Oil Prices: A Multifractal and Causality Analysis

The interaction between new energy vehicle (NEV) stock prices and the crude oil market is crucial for resource allocation and risk management. This study employs Multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the multifractal characteristics of the cross-correlation between Tesla stock price (TSLA) and crude oil price (Brent), as well as between TSLA and other NEV stocks (excluding TSLA). The experimental results reveal long-term persistence and multiple fractal characteristics in the cross-correlations. Additionally, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) demonstrates the asymmetry of the cross-correlation during upward or downward trends between TSLA and Brent, as well as between TSLA and other NEV stocks (excluding TSLA). Furthermore, utilizing the transfer entropy (TE) method, we assess the strength and direction of information flows between TSLA and Brent, and between TSLA and other NEV stocks (excluding TSLA). Interestingly, we observe bidirectional information transmission between TSLA and other NEV stocks, while only unidirectional information transmission from NIO to TSLA is evident. These findings provide valuable insights for resource allocation, supply chain management and sustainable development strategies for decision-makers in the NEV market.

Projections of private vehicle ownership, energy demand and vehicular emissions – a study of metropolitan cities in India

Urban agglomerations in India have witnessed significant growth in private vehicle ownership since the turn of this century. Intense urban road transport will have stern implications on air quality, GHG emissions, energy demands and, transport infrastructure. This study investigates the relationship between income and vehicle ownership rate for five metropolitan cities in India using a non-linear Gompertz functional framework. Medium-term scenarios of private vehicle (cars and two-wheelers) ownership, vehicle stock, energy demand and tailpipe emissions under multiple scenarios are envisaged by deriving ownership saturation based on city area and land use pattern. The results show a significant increase in vehicle stock resulting in a substantial rise in energy demand and vehicular emissions by 2035. However, the adoption of electric vehicles is expected to truncate this surge. Delhi is projected to saturate during this period while other cities are expected to saturate after 2035. The study also highlights transport policy and investment spheres to reduce private vehicle dependency.

Growth in the Worldwide Stock of E-Mobility Vehicles (by Technology and by Transport Mode) and the Worldwide Stock of Hydrogen Refueling Stations and Electric Charging Points between 2020 and 2022

This study discusses the portion of fuel cell electric vehicles (FCEVs) in the worldwide stock of vehicles on roads, particularly when compared to plug-in electric vehicles (PEVs), which comprise battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The study considers the overall number of these e-mobility (electric mobility) vehicles, as well as within each of 4 transport modes, namely: (1) passenger light-duty vehicles (PLDVs or simply “cars”), (2) light commercial vehicles (LCVs or simply “vans”), (3) buses, and (4) trucks. The study also investigates the progress in the number of hydrogen refueling stations (HRSs) for FCEVs, and contrasts that with electric charging points (ECPs) for PEVs; during the years 2020, 2021, and 2022. While the number of worldwide FCEVs nearly doubled in 2022 compared to 2020, the ratio of FCEVs to PEVs declined from 0.3348% in 2020 to 0.2738% (less than 0.3%) in 2022. In 2022 also, the number of FCEVs was 0.3914% (less than 0.4%) of the number of BEVs, and 0.9113% (less than 1%) of the number of PHEVs. The worldwide fraction of PEVs with respect to the total vehicles (both electric and non-electric) in 2022 was approximately 1.816% (split into 1.2704% for BEVs and 0.5456% for PHEVs), while the fraction of FCEVs was approximately 0.0050% (only 5 FCEVs per 100,000 vehicles). In terms of the convenience to supply the vehicles with energy, the number of worldwide hydrogen refueling stations nearly doubled in 2022 compared to 2020. Similarly, the worldwide number of electric charging points for use with PEVs nearly doubled in 2022 compared to 2020. However, the ratio of HRSs to ECPs declined from 0.0415% in 2020 to 0.0378% in 2022. The worldwide average FCEVs per HRS in 2022 was 70.69, while the worldwide average PEVs per ECP in 2022 was 9.75. Thus, PEVs are much more attractive than FCEVs for a driver concerned about the network of hydrogen stations. Furthermore, owners of PEVs have an additional option of recharging their vehicles at home (which is not applicable for FCEVs). Between 2020 and 2022, PEVs were dominated by BEVs, with 69.95% of PEVs being BEVs in 2022. This 2022 fraction of BEVs in PEVs reflects a consistent increase from the 2021 fraction (68.34%) and from the 2020 fraction (67.23%). Considering the worldwide increase in these e-mobility vehicles from 2020 to 2022, the number of FCEVs increased by a factor of 2.072, PHEVs increased by a factor of 2.322, and BEVs increased by a factor of 2.636, PEVs increased by a factor of 2.533. Thus, out of the 3 e-mobility vehicle technologies (FCEVs, PHEVs, and BEVs), BEVs had the strongest presence as well as the fastest growth.

China’s road transport decarbonization pathways and critical battery mineral demand under carbon neutrality

Decarbonizing road transport is important for China to achieve carbon neutrality. Road transport decarbonization requires rapid deployment of new energy vehicles, especially electric vehicles, expanding demand for critical battery minerals including lithium, cobalt, and nickel. By constructing a novel bottom-up framework that combines Low Emissions Analysis Platform and Vehicle Critical Mineral Demand model, this study assesses China’s road transport decarbonization pathways and critical battery mineral demand under three illustrative scenarios. Results show China’s vehicle stock peaking at 528 million in 2045 and remaining saturated through 2060. Except for diesel-fueled trucks, China’s internal combustion engine vehicles are completely phased out around 2050–2055. Share of oil-derived fuels in China’s road transport energy declines, while share of electricity and hydrogen increases significantly, with electricity and hydrogen together accounting for 57–88% in 2060. China’s road transport CO2 peaks at 977–1,083 Mt in 2028–2032, declining to 62–282 Mt in 2060, with private vehicles, light- and heavy-duty trucks as core mitigation areas. Cumulative demand for lithium, cobalt, and nickel from electric-vehicle batteries is estimated at 16.1–19.6 Mt LCE, 0.4–0.55 Mt and 3.3–4.3 Mt by 2060, respectively, indicating a challenge for China’s local mineral supply. Recycling reduces cumulative demand for primary lithium, cobalt, and nickel resources by over 30%, 60% and 60%, respectively.

Розробка нормативів витрат палива для міських автобусів та рекомендацій щодо ефективності їх використання

The basis of economical consumption of fuel and energy resources is the availability of a regulatory framework, which objectively reflects the conditions of operation of rolling stock of vehicles. The current rules are usually set by the average performance of cars and do not take into account the specific features of rolling stock. The article deals with the issues of fuel economy of city buses, taking into account real conditions of operation.
 The most fully studied issues of assessment of car qualities in established modes. However, the qualitative impact of factors for these modes on roads with a horizontal profile can vary significantly in real operating conditions. In this regard, the problem of studying the fuel economy of cars in unsuspecting and cyclic modes is relevant. The most difficult are cyclic modes of traffic with stops, which include almost all phases of traffic, which are found in operation of city buses, as well as all gearboxes used in this case.
 In order to solve the issues of rational use of fuel in road transport, it is important to improve the methods of calculating the indicators of fuel economy of cars in order to fully and accurately take into account the peculiarities of the process of their movement in different conditions of operation. In the development of fuel consumption standards, an analytical method was used, which is based on a strict mathematical model of diesel fuel consumption. The technique is based on a single classification of operating conditions, in which road and transport conditions are quantitatively assessed by the average technical speed, and atmospheric-climatic-pressure and ambient temperature.
 For the analysis, selection and justification of factors (parameters) for inclusion in the mathematical models of fuel consumption of buses, taking into account the conditions of operation, the equation of fuel consumption, proposed by prof. M. Ya. Govorushchenko for established movement.
 An important advantage of the developed methodology is the possibility of individual fuel consumption at road transport enterprises using simple computing equipment at the actual speeds of vehicles and daily air temperature.

Weighting Analysis of a Fund Portfolio of China's New Energy Vehicle Stocks

We studied the optimal weighting allocation for a portfolio of stocks in China's new energy vehicle industry, using data on circulation market value, price-to-earnings ratio P/E, growth of net profit after deductions, and institutional position share of the new energy industry for the three years 2019-2021. The return was also considered from the above four dimensions. Combining the above four dimensions, a better model for determining the weight of the new energy vehicle stock portfolio is obtained.

Carbon mitigation and health effects of fleet electrification in China’s Yangtze River Delta

Fleet electrification is one of the most promising strategies to mitigate carbon emissions and improve air quality. This study provides a comprehensive analysis of the currently unclear CO2 mitigation and human health benefits from electric vehicle (EV) adoption and energy decarbonization in the Yangtze River Delta (YRD) region by integrating fleet modeling, emission projection, air quality modeling and health risk assessment. Based on future socioeconomic trajectories, we project that the total vehicle stock in the YRD region will peak at 107–117 million around 2045–2050. The transition to EVs combined with largely renewable energy in the YRD region can potentially reduce CO2 emissions by 870 Tg in 2060 and brings along substantial health co-benefits with ∼360 avoided premature deaths per million from reduced PM2.5 and O3 concentrations. This study further explores the NO2-attributable burden from road transportation and reveals that fleet electrification could yield greater NO2-attributable health benefits than those from reduced PM2.5 and O3, especially in traffic-dense urban areas. Those findings indicate that China’s near-term energy development plans (35% renewable energy) have created the conditions for large-scale EV adoption. Our results imply that the benefits of EVs exhibit substantial spatial heterogeneity, underscoring the importance of region-specific EV incentive policies, and hint that policymakers should prioritize densely populated megacities to maximize the potential for public health gains.