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Exposure to airborne pollution has substantial adverse health consequences. Governments around the world have paid attention to this problem and started to take action to mitigate its harmful effects. In this paper, we investigate how a change in the consumption tax structure affects car emissions by exploiting exogenous variation from a natural experiment that took place in China. Our results show that this tax policy, which doubled the imposition paid on cars with large engines, reduced the emissions of all the pollutants studied, with the most significant decrease of 11% noted in Particulate Matter and Carbon Monoxide. These results have strong policy implications. By showing the effectiveness of this policy, we uncover the possible benefits of replicating it in different contexts. Further, by using information from COPERT, a totally new approach to evaluate tax and environmental policies, we propose new tools for policymakers to generate rich and detailed data that can be used in different contexts to evaluate policies where data from the population of automobiles is needed. [ABSTRACT FROM AUTHOR]

Extreme weather, especially typhoons, frequently impacts port operations, causing substantial economic losses. Thus, it has become vital to quantitatively evaluate the resilience of ports to typhoon disasters. This paper offers a comprehensive examination of the current evaluation methods used in assessing the resilience of ports and develops a quantitative port typhoon resilience assessment model based on the 4R (i.e., Reliability, Redundancy, Robustness, and Recoverability) framework. Ports' overall resilience to typhoon disasters can be assessed by integrating the analytic hierarchy process method, fuzzy logic, and the evidence reasoning approach. Four representative coastal ports in China were selected as case studies to examine the suitability and efficacy of the suggested model. This study provides innovative theoretical insights and empirical evidence to advance port resilience research, with a valuable reference for port administrators and policymakers, equipping them to address forthcoming challenges of climate change efficiently. [ABSTRACT FROM AUTHOR]

• Analyze the spatiotemporal variation of shared autonomous vehicle demand. • Consider demand uncertainty in mode choice and departure time choice. • Establish a two-stage joint optimization with the travel price and allowance. Shared Autonomous Vehicle (SAV) is an emerging travel mode that can reduce parking spaces and accelerate urban sprawl. The time–space varying demand leads to the imbalance between travel demand and vehicle supply. Using pricing to affect clients' mode choice is a key method for addressing the imbalance problem, which includes long-term pricing and short-term allowance. Hence, in this paper, we propose an innovative method to enhance the SAV utilization rate while considering stochastic demand: fixed price on population mode choice and real-time allowance on personal departure time choice. A mixed integer nonlinear program is formulated to maximize the total profits of SAV operators. To solve this model, a customized gradient search algorithm is proposed. A case study is conducted in Suzhou Industrial Park, China. It reveals the impacts on travel demand and departure time choices and discusses the impacts and policy-making for SAV applications. [ABSTRACT FROM AUTHOR]

The development of dry ports has reshaped the international freight shipping market, introducing both competition pressure (i.e., the common hinterland) and cooperation opportunities (sea-rail intermodal) for seaports. This is more evident in China with the development of the China Railway Express. Unlike dry ports, seaports are more vulnerable to climate change-related disasters, calling for investment in adaptation measures. This paper examines how co-opetition with the dry port affects seaport adaptation investment using a two-stage game-theoretical economic model. Results indicate that cooperation leads to more seaport adaptation investment, while competition results in reduced investment. When compared to the social optimal level of adaptation investment, the seaport tends to under-invest (over-invest) when the cooperation (competition) market size is larger. We also analyze how government subsidies in the seaport's adaptation help achieve optimal social adaptation and how the Knightian uncertainty of the disaster occurrence affects seaport adaptation investments. The relevant policy implications are also discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] To achieve carbon neutrality, it is urgent to quantify carbon emissions to support policy deployment. Based on life cycle assessment, this paper proposed calculation method for carbon emissions from road infrastructure in a Demonstration Zone, China. Based on scenario analysis, this paper quantified the carbon emissions currently and analyzed the trend and characteristics of carbon emissions of road infrastructure from 2020 to 2060 through 4 scenarios. The results show the carbon emissions fluctuate between 20 kt and 540 kt CO 2 from 2013 to 2019 and increase significantly in 2014 due to the surge in road mileage. In the first three scenarios, the carbon emissions show an increasing trend after 2030, with annual growth rates of 1.12%, 0.57%, and 0.27% respectively. However, in the optimal scenario, the peak year of carbon emissions is 2024, with the peak emissions of 649.333 kt CO 2 and an increase of 245% over the base year. [ABSTRACT FROM AUTHOR]

The increasing of carbon emissions due to traffic congestion in urban centers has been plaguing city managers. Park-and-Ride system are considered as important solutions to reduce urban carbon emissions. However, research on parking reservation on park-and-ride systems is still insufficient. Therefore, this paper explores the impact of parking reservation mechanisms on park-and-ride systems. A multi-modal agent-based network model is constructed to simulate the park-and-ride behavior, different parking reservation strategies are assessed and optimized which aim to minimize carbon emissions. Taking the Suzhou Guanqian Street Commercial District, China as the numerical example, we analyzed the impact of parking space allocation on carbon emissions. When parking spaces are reserved in proportion to demand, emissions decrease until a 70% reservation ratio. Beyond this threshold, emissions increase. Employing Genetic Algorithm (G.A.) to optimize the allocation of reserved parking spaces in each parking lot can further reduce carbon emissions. [ABSTRACT FROM AUTHOR]

In the 21st century, China is experiencing rapid economic growth alongside increasing car ownership and its attendant challenges. However, little is known about the determinants of expenditure on car acquisition and household car ownership in China, especially their dynamics as this motorization process has taken place. In this paper, we present household car ownership and expenditure analyses using a unique panel dataset, the China Household Finance Survey (CHFS). We identify three clusters of households with distinct income and expenditure characteristics consistently existing from 2011 to 2017. We also demonstrate distinctive temporal patterns in expenditure in the periods prior to, at-time-of, and following car acquisition for car-purchasing households. We report that most, but not all, determinants we studied have been stable over time. Finally, contrary to contemporary findings in Western countries, being a younger-aged household is positively associated with car ownership, while living in rural areas has a negative association. [ABSTRACT FROM AUTHOR]

In view of the climate emergency, it is necessary to model and forecast road transport emissions for implementing more effective climate policy. This paper fills an important research gap by quantifying the challenges, barriers and remedies of achieving road transport emission reduction and air quality improvement in developing countries. It contributes to the debate on top-down and bottom-up approaches to reconcile carbon and other transport related emissions. China and India are chosen as case studies. Using various official statistics and proxy variables, we estimate and compare the road transport carbon emissions of the two countries systematically from 2009 to 2020. Insights from detailed mode-specific estimations of the bottom-up approach are valuable for targeted policies and measures. An analysis of the major components of road transport carbon emissions points to strategies of promoting electric vehicles, reducing transport demand, accelerating modal shift to low-carbon modes, and cleaner electricity to achieve climate policy. [ABSTRACT FROM AUTHOR]

The development of BEVs (battery electric vehicles) can significantly mitigate the dependence on fossil fuels and reduce carbon emissions. To advance the development of BEVs, China is adjusting the subsidy and dual-credit policies. This paper addresses these two issues to help policymakers determine effective policies. Through the simulation with a system dynamics model that incorporates the government, automakers, infrastructure operators, and consumers, we find that (1) reducing the overall level of subsidies has a minor impact on the development of BEVs in the long term; (2) subsiding the construction of infrastructure, especially battery swapping stations, will produce better effects than others; (3) the proposed carbon quota mechanism, which is in line with the unified carbon market, is more conducive to the diffusion of BEVs and carbon reduction than the dual-credit policy. Our MLP-SD (multi-level perspective system dynamics) model broadens the analytical perspective of the technology transition in the automobile industry. [ABSTRACT FROM AUTHOR]

As a major carbon-emitting sector, transportation promotes regional linkages and triggers embodied CO 2 flows that accompany trade. This paper first constructs a 'provincial-national-global' multi-scale input–output (MSIO) model based on IO-nested technology. Then it evaluates the embodied CO 2 in transportation-related trade (TTEC) flows between Chinese provinces and Belt and Road Initiative (BRI) countries, and assesses their driving factors from multi-scale regional and cross-sectoral. Empirical findings show that regions with large TTEC flows are mainly concentrated in the northeastern, eastern and southern areas of China. The construction sector is the largest contributor to exported TTEC, while the energy sector has the largest imported TTEC. Singapore and India are the main exporting countries of TTEC from China, and India and Russia occupy a dominant position in importing TTEC. Finally, policy implications are put forward, that should provide quantitative and theoretical support for decision-making on reducing carbon in transportation between China and BRI regions. [ABSTRACT FROM AUTHOR]

The development of electric vehicles (EVs) is expected to play an important role in achieving the emission reduction targets in the transportation sector by many countries and regions, including China's dual carbon goals. A bottleneck to the mass roll-out of EVs is the limited charging facilities. This paper considers the planning of charging facilities for a new developing area in a metropolis, and an optimization model for charging station planning based on the dynamic transportation system is proposed. The proposed model is developed using an objective framework that considers the spatio-temporal characteristics of EV charging demand in order to minimize the overall cost while the constraints from suppliers and drivers are met. The Voronoi diagram is used to determine the final service boundary of each charging station, and the effect is verified in the planning of charge stations for the Yizhuang new town in Beijing. The case study confirms that the proposed method can optimize the charging facilities that fit well with the traffic network conditions. Furthermore, it is shown that the charging demand varies in accordance with the population density and regional functionality in different areas. [ABSTRACT FROM AUTHOR]

Although the built environment–travel connection has been extensively examined in urban settings, evidence from rural and small towns is still scarce. This paper addresses this gap by exploring the influence of the built environment on travel mode choice using national-level survey data from 119 rural towns throughout China. The results show that rural built environment variables significantly influence mode choice, with socioeconomic, regional economic and natural environment factors controlled: at regional level, close proximity to county centres, highways and bus stops tend to reduce car dependence. At local level, small-scale, compact, and mixed land use encourage walking and bus use. The built environment influences mode choices for shopping trips more than commuting trips. The results suggest that spatial planning for land use and transport networks will be effective in shaping greener travel and sustainable transport development in rural areas of China and in developing countries with similar contexts. [ABSTRACT FROM AUTHOR]

Although operational activities in the aviation sector inevitably bring more emissions, they also reshape the structure of the regional economy, and often upgrade emission-heavy industries to cleaner service sectors. Thus, the overall impact of aviation network development on the region's environmental trajectory is unclear, and calls for rigorous empirical study. Using the data of 283 Chinese prefecture-level cities for the period 2003–2017, this paper proposes and calculates a comprehensive "carbon lock-in" index to measure cities' reliance on emission-heavy sectors and resistance to emission reduction. Then, we calculate cities' air connectivity and network centrality to measure the aviation development, and also examine their direct, indirect, as well as heterogeneous impacts on cities' carbon lock-in. Our empirical results suggest that an improved aviation network development helps alleviate carbon lock-in. Mechanism analysis further reveals that fixed input, industrial structure upgrading, and technological innovation are the three underlying channels. [ABSTRACT FROM AUTHOR]

Transportation systems are fragile when facing various natural hazards. To analyze the performance of these systems under disruption, this paper provides a holistic multi-phase model to assess the resilience of a transportation system consisting of multiple modes. The hazard scenarios for modeling strikes of typhoons are generated by the Spatially Localized Failure (SLF) model and Monte Carlo simulation. Then based on the simulation of typhoon scenarios, we assess the resilience of both single-mode systems and a complementary system of multiple modes. This method is applied to the high-speed rail network and civil aviation network in China under different typhoon intensity scenarios. Results show the different resilience characteristics of the two networks, and more importantly unveil the complementary effect between the two modes when suffering from damages. The improvement of system resilience due to the complementary effects provides a motivation for promoting cooperation between high-speed rail and civil aviation. [ABSTRACT FROM AUTHOR]

Road traffic has changed as an essential source of influential urban air pollution in China. This study developed the Spatial Durbin Model to analyze the spatial spillover effects on air pollution caused by urban transportation infrastructure. The results show that high-emission areas congregate in the eastern region of China, which reflects noticeable spatial spillover effects and agglomeration characteristics as high-emission "clubs." When the traffic construction 1 1 Traffic construction area refer to the acreage of street area within the city in this paper. area increases by 1%, the air pollution level will increase 3.2% as accompanied. The improvement of the transportation infrastructure will bring out economic development. The speed of air pollution generated by the resources consumed by economic development is higher than that of technological improvement in the economic transition period to reduce air pollution. In contrast, economic growth and air pollution exacerbation represent a U-shaped curve connection. Most provinces remain in a stage where air pollution worsened with economic growth. [ABSTRACT FROM AUTHOR]

• Assess the route redundancy of freeway networks in mega-city regions. • Propose diversity and dispersion of alternative paths as two complementary measures. • Assess route redundancy of mega-city freeway networks at network and city levels. • Consider three major mega-city regions of China in the case studies. In this paper, we investigate the performance of freeway networks in mega-city regions from the perspective of route redundancy—the provision of alternative routes for travelers when their primary routes are disrupted by disasters. Specifically, route redundancy is assessed with two complementary dimensions: the diversity and dispersion of alternative routes. The former represents the number of alternative routes without disruptions, and the latter reflects the robustness of this number during disruptions. Three typical mega-city regions in China, namely the Beijing-Tianjin-Hebei, the Guangdong-Hong Kong-Macao Greater Bay Area, and the Yangtze River Delta—are examined as case studies. Results indicate that travelers in first-tier cities (i.e., national economic or political centers) may have inadequate route redundancy. Route diversity increases when more topological cycles are traversed by numerous alternative routes. Additionally, alternative routes of the peripheral cities in mega-city regions are less dispersed, which cause their lack of redundancy and should be improved. [ABSTRACT FROM AUTHOR]

Low-carbon travel for rural residents in China is of great significance for reducing CO 2 emissions and achieving the "dual carbon goals". This paper uses system dynamics modeling and case analysis to explore the realization path of low-carbon travel in rural China, establishes a complex system dynamics model of low-carbon rural travel in China. By running multi-scenario simulations, the characteristics of rural residents' travel and the trend of CO 2 emissions in China are found. Through the case study, it is found that the built environment, low-carbon travel policy, rural residents' travel preference and travel cost are the important factors affecting rural low-carbon travel. New energy policy can effectively reduce rural travel CO 2 emissions. However, an excessively large increase in rural low-carbon public transport would reduce marginal benefits. The government should choose the right policy intensity according to the economic and fiscal situation. [ABSTRACT FROM AUTHOR]

• Explore spatial patterns and determinants of on-demand food delivery (ODFD) usage. • Use auxiliary datasets and prior knowledge to downscale ODFD usage to 100-m grids. • ODFD usage largely concentrates in more urbanised areas, especially city centres. • Food accessibility and built environment are critical determinants of ODFD usage. • Several factors' impact magnitudes differ between more and less urbanised areas. On-demand food delivery (ODFD) services now produce many motorised trips in Chinese cities that raises environmental concerns. It is therefore crucial to understand where people use ODFD and what factors influence their usage. This paper explores the spatial patterns and determinants of ODFD usage in Shenzhen, China, focusing on the roles of food accessibility and the built environment. The results show that ODFD usage concentrates in more urbanised areas, especially city centres and sub-centres. Furthermore, more ODFD orders are generated in areas with lower food accessibility by walking and higher food accessibility by cycling, as well as in areas with higher population density, lower point of interest (POI) density, lower intersection density, higher street density, higher land use mix, higher percentage of land used for urban residences and commerce, and lower percentage of land used for rural residences, industries, and green space. These findings provide evidence-based implications for ODFD regulation. [ABSTRACT FROM AUTHOR]