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• The paper investigates the impact of highway extension on new building construction. • The investigation focuses on a project that aims to limit land use change. • The infrastructure increases the probability of construction on surrounding parcels. • The impact is spatially concentrated around the access ramp and along the highway. Despite its impact on both sprawl and carbon emissions, developing or expanding highway infrastructure remains the object of strong political support. Highway access provides important advantages for firms and households, generating powerful incentives to develop new built areas through the conversion of vacant land. Based on the case study of the expansion of Highway 30 on Montréal's South Shore region between 2000 and 2019, this paper investigates how new highway infrastructure impacts the construction of new industrial and commercial buildings on individual parcels. Using a panel dataset, an event study model is developed to estimate the impact of the proximity to highway access ramps on the probability of construction. Results show that highway infrastructure increases the probability of construction of new industrial and commercial buildings, even if public authorities aim to limit such possibilities by legal constraints and laws. [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 electric two-wheeler (E2W) niche in India has undergone substantial changes over the years due to a combination of global and local factors such as battery technology developments, consistent policy support, increasing fuel prices, and favourable consumer perception of E2Ws. As markets for new technologies grow, the nature and intensity of their interactions with the broader socio-political milieu change, which necessitates recalibration of governance strategies for their further growth. This paper employs the Multi-level perspective (MLP) approach to study the evolution of the E2W socio-technical system and finds that due to favourable developments, the E2W market is expanding and appears to be at the cusp of a significant transition. This provides a window of opportunity and to leverage this, the paper argues that the nature and scope of the policy support needs re-orientation from focusing only on supporting niche to also including regime destabilizing instruments in the policy toolkit. [ABSTRACT FROM AUTHOR]

Developed countries have already implemented a vehicle scrap policy that prevents the on-road usage of old vehicles beyond a certain age to curtail pollution. Recently Indian government also announced its plans and policies for vehicle scraping. There is a multitude of barriers to the implementation of such a policy in India. This paper identifies and models all implementation barriers. Literature review and interactions with various stakeholders helped to identify the barriers. The identified barriers are processed with a hybrid methodology, which is a combination of the Fuzzy Analytic Hierarchy process and the Decision-Making Trial and Evaluation Laboratory. The data is modeled in a fuzzy context to account for issues of ambiguity and subjectivity. This study helps policymakers and other stakeholders by identifying the barriers to vehicle scrap policy implementation in India. Furthermore, this paper offers insights for future research in developing policies and practices for India's emerging vehicle scrap business. [ABSTRACT FROM AUTHOR]

COVID-19 has brought severe disruption and demand suppression to mobility, especially to public transport (PT). A key challenge now is to restore trust that PT is safe again. This paper investigates pandemic impacts on PT safety and stress perceptions in three Nordic cities, drawing on 2018 and 2020 survey data analysed in structural equation models. While finding modest pandemic effects on safety and stress perceptions overall, strong heterogeneities exist across gender, age and geographic categories. Women perceive less PT safety and more stress, especially during the pandemic. Older adults reduced PT more during the pandemic and perceived no stress reduction like younger adults. Stockholm travellers feel less safe and more stressed than in Oslo and Bergen, whilst pandemic PT use and perceived safety reductions are least in Bergen. The paper discusses the long-term implications for theory and policy across multiple mobility scenarios accounting for modal change and travel demand uncertainties. [ABSTRACT FROM AUTHOR]

Reliable assessment of the resilience of transportation networks to natural disasters is a prominent issue. This paper investigates how the spatial feature of natural disasters affects the resilience of transportation networks. Our research reveals that incorporating spatial feature data on disaster impacts is highly important for assessing network resilience. More precisely, the uncertainty linked to the estimation of the resilience index in the context of disaster-induced interruptions with spatial feature significantly exceeds that of conventional approaches. We present an illustrative case of a transportation network affected by a hurricane. The results reveal that the improved characteristics of disaster-induced outages greatly alter the manner in which the network recovers, including changes in emergency system characteristics. Our research indicates that extant methodologies employed for evaluating the resilience of critical infrastructure potentially inflate the confidence levels pertaining to network recovery predictions, primarily owing to insufficient attention given to the spatial configuration of disasters. [ABSTRACT FROM AUTHOR]

Environmental justice – the concept that environmental amenities and burdens should be shared equitably among all races and socioeconomic classes – has gained diplomatic traction internationally, and political traction domestically in the United States, in recent years. In this paper, we focus on developing federal policy relevant to transportation project planning and operation in the U.S.; however, these developments reflect international issues of inequity associated with climate change and environmental burdens. First, we provide an overview of federal policy initiatives related to environmental justice, including President Biden's Justice40 initiative. Then, we examine the U.S. National Environmental Policy Act (NEPA) as a potential avenue for mandating environmental justice assessment in the transportation industry, through the lenses of both procedural and distributive justice. Finally, we review several publicly available online Geographical Information System (GIS) tools that were recently developed for purposes of expanding public and governmental understanding of environmental justice challenges, and provide decision support for users to incorporate these tools into the environmental impact assessment process for transportation projects. [ABSTRACT FROM AUTHOR]

Climate change impacts such as extreme temperatures, snow and ice, flooding, and sea level rise posed significant threats to railway infrastructure networks. One of the important questions that infrastructure managers need to answer is, "How will maintenance costs be affected due to climate change in different climate change scenarios?" This paper proposes an approach to estimate the implication of climate change on the life cycle cost (LCC) of railways infrastructure assets. The proportional hazard model is employed to capture the dynamic effects of climate change on reliability parameters and LCC of railway assets. A use-case from a railway in North Sweden is analyzed to validate the proposed process using data collected over 18 years. The results have shown that precipitation, temperature, and humidity are significant weather factors in selected use-case. Furthermore, our analyses show that LCC under future climate scenarios will be about 11 % higher than LCC without climate impacts. [ABSTRACT FROM AUTHOR]

The Euro 7 standard is expected to intensify its focus on real-driving emissions compliance thanks to the on-board monitoring (OBM) system. OBM is designed to bridge the gap between emission limits and real-world vehicle emissions by continuously monitoring their levels using on-board sensors and models. Essentially, this system aims to verify vehicles compliance, prompt timely repairs otherwise, and provide authorities with emissions data for fleet inspection. Leveraging a large real-driving emissions database from an in-service Euro 6d-Temp vehicle, this paper reviews the current OBM proposal and discusses its possible outcomes and challenges using available sensor technology. • The Euro 7 on-board monitoring concept is reviewed and discussed. • On-board monitoring emissions assessment is analyzed with real-driving data. • Challenging aspects regarding the correct emissions estimation are highlighted. • More than 60% of the NOx trip information can be lost due to sensor light-off delay. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions lead to climate change, subjecting the maritime environment to severe threats. In response, globally, states and organizations are taking actions to decarbonize. In this context, this paper builds an evolutionary game analysis involving the government and shipping company under a governance framework with IMO, from a perspective of economic regulations, and explores how to establish a proper shipping decarbonization mechanism and implementation plans in the process of dynamic evolution. Based on a system dynamics simulation model, we analyzed how the cap-and-trade policy system, tax-and-subsidy policy system, and cooperative policy system perform in terms of shipping decarbonization and the role of IMO in shipping decarbonization. Our research proves that the cooperative system is more efficient and stable in decarbonization than singular economic regulations; static and dynamic implementation plans should be coordinated in different stages; and finally, IMO plays an active role in multi-agent coordinated controls. [ABSTRACT FROM AUTHOR]

This paper evaluates Integrated-Demand Responsive Transport (I-DRT) as a solution to the challenges faced by traditional public transport (PT) systems in low-demand urban areas. The study investigates the implications of replacing local PT with I-DRT in low-demand urban areas. A multi-objective model, incorporating operational cost, environmental impact, passengers' travel time, and inequity is used to simulate the I-DRT performance. The analysis compares the performance of I-DRT and existing local bus lines in Belconnen, Canberra, Australia, based on number of utilised vehicles, operational cost, fuel consumption, average travel time, individual passenger travel time, delay, and inequity in delay distribution. [ABSTRACT FROM AUTHOR]

Freight transport decarbonization is challenging due to the slow implementation of policies to meet climate goals. This paper analyzes the dynamics of the implementation of freight decarbonization measures. A System Dynamics model was developed and applied to the Brazilian freight system to simulate the use of more sustainable modes and means of transport, including electrification, increased use of biofuels, acceleration of fleet renewal, and modal shift. Significant emission reductions are found in the scenarios combining a shift to alternative modes and a rapid phase-out of diesel vehicles. Even so, the Brazilian freight sector's emission budgets towards limiting global warming to 1.5 °C and 2 °C will be depleted during the current and next decade, respectively. An absolute reduction of carbon emissions before 2050 seems unlikely. Besides confirming the need to study the dynamics of the freight system, the findings corroborate the urgency for stronger actions on freight decarbonization. [ABSTRACT FROM AUTHOR]

The lack of information on trip purpose and alternative mode in micromobility service usage data remains a major analytical challenge. Conventional survey method is subject to significant sampling and stated preference biases. To overcome this challenge, this paper presents a new inference method through a case study of rental e-scooters in London. The inference method features a rule-based algorithm for matching observed rental e-scooter trips with filtered trip samples in the English National Travel Survey (NTS) series. Probability distribution of trip purposes and alternative modes are then retrieved from NTS. Inference results are validated using official data. Discrepancies, sources of biases and correction measures are investigated. Based on the inferred mode substitution pattern, we estimate greenhouse gas emissions reduction of selected rental e-scooter trips in London (36–103 g CO 2 e per mile). It is expected that the proposed method is applicable to a wide range of micromobility studies using service usage data. [ABSTRACT FROM AUTHOR]

The growing concern over air pollution and community health, demands a comprehensive understanding of the political nature of transport-related emissions. This paper approaches how structures of power influence travel behaviour and, consequently, how they shape emissions from mobility in Barcelona. To comprehend how the intersection of gender, age, and migration background influences air pollution, we use a travel survey to build a set of models that are known to theoretically engage with intersectionality studies. Results show that identities tied to structures of power promote a greater contribution to air pollution than other mechanisms. That is, middle-aged European-born men have the most NO x -intensive mobility practices. In contrast, people that embody intersectional experiences of oppression such as misogyny, racism, or ageism, have lower emission levels. Considering these results, we argue that policies which acknowledge the unequal distribution of responsibilities present an opportunity to reduce emissions from transportation, while guaranteeing fairness and advancing environmental justice. [ABSTRACT FROM AUTHOR]

Accessibility-oriented development (AOD) strategies are the extension of transit-oriented development (TOD) strategies but focus more on access to destinations. Adopting AOD strategies can help identify and improve the defects of imperfect TOD construction. Based on AOD strategies, this paper evaluated the comprehensive accessibility to multiple public facilities with the Gaussian-based two-step floating catchment area method (G2SFCA) in the heart area of Chengdu City and further analyzed its equity issues. The comprehensive accessibility analysis proved the efficiency of AOD-based analysis in public resources shortage area determination and TOD level evaluation. The equity analysis indicated that the improvement of equity could not reflect the progress on total accessibility but only rationalize the allocation structure of public resources. Based on the case study, several suggestions for policy-making are given, including the construction of the non-motorized transportation system, adjustment of supply allocation, and comprehensive consideration of equity and accessibility in urban planning. [ABSTRACT FROM AUTHOR]

• One of the most sparsely populated areas in Europe. • Long distances to services and other destinations for daily activities. • Two villages were selected due to ongoing DiSS initiatives. • The results support the idea that DiSS could be a viable solution to mitigate and counteract accessibility poverty in rural areas. • DiSS for reducing long-distance private car journeys in reducing greenhouse gas emissions. • Essential to support older people in adopting digital solutions for a more sustainable digital transition. Norrbotten region is one of the most sparsely populated areas in Europe, with often long distances to services. This paper aims to gain a deeper understanding of the everyday mobilities in later life in rural areas, and to assess to what extent digital service solutions (DiSS) can contribute to reduced accessibility poverty. The study focuses on how DiSS contribute to more equitable accessibility by means of a case study in two villages, selected due to implemented DiSS (store with digital locks, digital hubs, etc.). Interviews with older people and other informants show the potential of DiSS to counteract accessibility poverty by bringing services nearer to home and reducing the need for longer trips, while contributing to the creation of healthier and more resilient environments. If implemented carefully, DiSS can have the potential to contribute to the development of more transport-efficient and socially just societies. [ABSTRACT FROM AUTHOR]

This paper examines individual preferences for a reduction of life-cycle CO 2 emissions in vehicle purchase decisions. The empirical analysis is based on data from a stated choice experiment among citizens in Germany that refers to decisions between three types of electric vehicles and one conventional vehicle that are characterized by several attributes. With respect to CO 2 emissions, we specifically examine emissions in vehicle production besides the commonly considered emissions in vehicle use. Our econometric analysis reveals a strong stated preference for the reduction of both components of life-cycle CO 2 emissions. Furthermore, we find that conventional vehicles are significantly preferred over electric vehicles. Surprisingly, environmental attitudes, i.e. environmental awareness and ecological policy identification, have no significant effects on the reduction of CO 2 emissions. Instead, citizens with a strong environmental identity rather tend to avoid the purchase of conventional vehicles. We discuss several practical policy implications. [ABSTRACT FROM AUTHOR]

• Influence of driving behavior on fuel efficiency is analyzed. • Volatility used as a surrogate for identifying driving behavior. • K-means, K-medoids and hierarchical clustering used to classify driving behavior. • Powertrain drive cycle simulations used to assess fuel efficiency and emissions. • Aggressive driving observed to create 23% increase in fuel consumption. Consumption of fossil fuel-based energy for vehicle propulsion and associated emissions are a global concern. One pathway to energy reduction is to examine situations where high-energy consumption occurs on roadways, e.g., speed volatility at work zones, or on sharp curves, which has been understudied. Harnessing second-by-second data from the naturalistic driving study and using the concept of driving volatility, this paper explores driving styles in work-zones and curves using machine learning approaches (k-medoids, hierarchical clustering) and drive-cycle simulations from Autonomie®. Results show that aggressive driving account for 12.2 % and 15.4 % of events that occurred in work zones and on curves and leads to 23 % increase in fuel consumption as opposed to normal driving. These results have implications for transportation agencies to improve work-zone configurations and provide signage or technology on curves to reduce fuel consumption and emissions. Moreover, automated and connected vehicles can smooth out traffic flow with advanced advisories and warnings. [ABSTRACT FROM AUTHOR]

Accurate identification of the spatial and temporal dynamic impacts of disasters on road networks is crucial for making informed decisions regarding postdisaster emergency response and recovery. In this paper, we propose a multidimensional vulnerability assessment framework that utilizes time series crowdsourced data. The framework enables a spatiotemporal analysis of traffic flows at the link level, allowing us to identify the primary factors that contribute to vulnerability after a disaster. The results show that there is a significant variation in link vulnerability over time, with the overall network gradually returning to a normal state. We also observe a global correlation in link vulnerability across the spatial aspect, although the autocorrelation effect is only present among directly contiguous links. Furthermore, metrics affecting link vulnerability varied during different periods of response. Graph-based metrics of road network structure, population density, and road type are key factors influencing postearthquake vulnerability. [ABSTRACT FROM AUTHOR]

With the increasing popularity of electric buses (EBs), accurate estimation of the trip-level energy consumption of EBs has become increasingly essential. In this paper, an effective energy consumption estimation approach was proposed based on real-world operation data of EBs. Operation data of EBs from 3 different bus routes were collected and pre-processed to extract energy consumption-related features from various aspects such as traffic condition, environment, vehicle status and driving behaviour. The analyses of feature distribution, feature interaction and feature importance were then carried out. And the contributions of features to energy consumption were thoroughly analysed by Shapley value. Finally, different machine learning models were built and compared. The optimal results achieved an MAPE of 4.404% under 10-fold cross-validation, with an improvement of at least 29% over existing studies on the subject. [ABSTRACT FROM AUTHOR]

Shore power (SP) is a key technology to reduce emissions in a port. The deployment of SP has faced a significant challenge due to its high management costs. This study aims to compare various incentive policies that can promote SP from the perspectives of pollutant penalty, berth allocation, construction subsidy, electricity subsidy, and their combinations. To identify effective incentive policies for wide use of SP from both sides, this paper develops a cost-minimizing nonlinear mixed-integer programming model. The model optimizes decisions regarding SP deployment, berth allocation, and ship service sorting simultaneously. The performance of these incentive policies is evaluated in a bulk terminal scenario. Sensitivity analysis of key parameters was conducted to examine the impact of policies. The results show that all the proposed policies can effectively promote SP use and emissions reduction. Policymakers are recommended to implement a mixed incentive policy instead of a single incentive policy. [ABSTRACT FROM AUTHOR]

Inequitable distribution of public electric vehicle (EV) charging facilities may result in disparities in charging accessibility, potentially impeding the uptake of EVs. In response, this paper proposes an analytical framework to assess the accessibility-based equity of public EV charging infrastructure systematically, using Hong Kong (HK) as the study area. The results demonstrated severe spatial inequity of charging facilities in central, north, and southwest HK. Meanwhile, the Gini index of all public EV charger types for the total population was 0.751, and the indices for low-income, low-education level, and government-funded housing subgroups were 0.791, 0.809, and 0.893, respectively. These indicated considerable horizontal and vertical inequity from a statistical perspective. Furthermore, age, education level, family structure, and housing type were identified as significant socio-demographic characteristics correlated to the accessibility-based equity of public EV charging infrastructure in HK. These findings are expected to be useful for future policymaking and infrastructure planning. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are expected to revolutionise transport worldwide and transform urban life. However, there are many unknowns concerning the impacts of these technologies in terms of sustainability, justice, and safety. It has been suggested that CAVs may exacerbate inequities and safety disparities concerning the interaction of vulnerable road users (VRUs) with motorised transport. This paper investigates the justice issues that CAVs policy needs to address concerning VRUs. Our approach to studying CAVs' capabilities and their potential perverse outcomes uses transport justice as an evaluative framework. The justice-related outcomes discussed include: traffic injuries, impact on sharing road responsibilities, loss of on-street space, access to technology, inclusion for disabled and older adults, CAV technological development, and impact of congestion and air pollution. The paper proposes a future research agenda emphasising areas where CAVs may positively impact VRUs. [ABSTRACT FROM AUTHOR]

Simulation is a valuable prediction tool to evaluate the impact of climate change interventions prior to disruptive implementations that may yield unintended and unwanted consequences. Advances in agent-based simulation allow us to estimate the dynamic emissions produced by vehicles at a fine resolution, with each vehicle modelled individually. The scalability of these models allow decision-makers to evaluate large-scale scenarios. But how good are these models? In this paper, the authors apply a state-of-the-art emissions model in the Multi Agent Transport Simulation (MATSim) framework to simulate individual vehicle emissions. Simulation results are compared with real driving emissions tests, using a portable emissions measurement device on a light and heavy vehicle. Quantifying the gap between macro-level simulation and actual emissions, the paper contributes by showing that pollutants are significantly underestimated, especially for heavy vehicles. This confirms prior micro-scale studies and magnifies the detrimental impact of using uncorrected aggregated models to inform environmental policy affecting transport. • Quantifying the gap in emission estimates on large-scale traffic simulations. • City-scale activity-based transport model coupled with vehicle-specific emissions. • Variation in real driving emissions is much larger than in randomised simulations. • Macro-level models underestimate heavy vehicle emissions more than light vehicles. [ABSTRACT FROM AUTHOR]

[Display omitted] • Reviewed + 200 research papers related to geopolymer concrete. • Utilization of industrial waste and recycled aggregates in geopolymer concrete is focused. • 12 M + molarity of sodium hydroxide is efficient for geopolymer based concrete pavements. • Geopolymer based rigid pavements ensure a cleaner environment. After industrial sector, construction sector utilizes significant quantity of natural raw materials and energy sources. Construction sector waste needs dumping spaces whereas the industrial sector waste like, fly ash and coal bottom ash poses health hazards as they contaminate water, air and soil. Pozzolanic concrete utilizes industrial waste by substituting a portion of cement (<60 %) and offers better durability with similar mechanical properties to normal concrete. Geopolymer concrete, a durable and high-strength concrete, has been devised to fully substitute cement with industrial wastes. This study reviews the requisites of geopolymer concrete to perform like pavement quality concrete while utilizing maximum quantity of wastes in both the binder and aggregate phase. This paper concludes that geopolymer concrete can be used in pavements even with more than 50 % virgin aggregate substitution with recycled aggregates. Further, the mix should be enriched with ground granulated blast furnace slag with sodium hydroxide molarity within 12–16. [ABSTRACT FROM AUTHOR]

The integrated air-bus service expands the catchment area and alleviates congestion of regional airports. To gain further insights into the unexplored potential attributes of the integrated service that generate passenger satisfaction, this paper utilizes a two-stage analysis approach to identify the key promotion factors for passengers from different constituents. Based on the survey data collected in Nanjing Lukou International Airport, this paper 1) uses k-means clustering to categorize respondents into four groups. 2) Combines the gradient boosting decision tree and impact asymmetry analysis to identify the attributes that have nonlinear influences on the overall service satisfaction for each group respectively. Results suggest that the timetable of the airport bus is critical for all passenger groups. Interestingly, there are noticeable differences in passenger satisfaction with the accessibility, cost affordability, comfort, reliability, and integration of the integrated service, providing the basis for customizing service promotion strategies among different passenger groups and airports. [ABSTRACT FROM AUTHOR]

As modern cities expand, parcel carriers are obliged to deal with the various last-mile challenges of the urban setting, in order to meet the ever-increasing requirements of consumers while ensuring an eco-friendly distribution system. Some of the urban last-mile challenges, such as kerbside parking limitations and vehicle access restrictions, pose additional constraints to carriers that operate van-based deliveries. This paper describes a new distribution model and an associated optimisation problem, namely a vehicle routing problem with portering (VRP-P) with time windows, that integrates on-foot porters with cargo vans. In this distribution strategy, vans rendezvous with porters at handover points at selected customer locations where the transfer of parcels can take place, avoiding the need for designated parking spaces. The VRP-P is modelled as a mixed-integer linear programming formulation and solved on real delivery data in central London. The paper also describes a fast heuristic that uses several improvement operators. Computational results show that the use of portering yields time and carbon savings of up to 89%, depending on the number of customers served. The heuristic obtains high-quality feasible solutions in short computational times and outperforms a commercial optimiser on large scale instances. The findings also show high utilisation of portering even at limited parcel carrying capacities. • We describe an urban delivery system that integrates routing of vans and porters. • We introduce a new mixed-integer linear programming model to solve the problem. • An actual data set from London deliveries is used for analysis. • We propose an efficient heuristic which produces results in short computational time. • Portering achieves up to 50% and 89% time and carbon savings, respectively. [ABSTRACT FROM AUTHOR]

This paper explores the potential of aggregated traffic models based on the Macroscopic Fundamental Diagram for building a network-wide monitoring system of travel emissions. Such a system consists of two layers. In a bottom layer, an aggregated traffic model predicts the network dynamics. In a top layer, an emission model estimates the total exhaust emissions. This paper discusses how to properly calibrate the aggregated traffic models of the bottom layer, to then estimate the total network emissions. We focus on the calibration of travel distances and the network partition definition. We propose a methodology that utilizes the concept of the detour ratio as a proxy to model real travel distances within the aggregated traffic models. This methodology increases the effectiveness of aggregated traffic models for predicting network-wide emissions in realistic scenarios. We also show that the definition of the network partitioning can significantly influence the total network emissions estimation. • We leverage our knowledge of the MFD dynamics for estimating total network emissions. • A microscopic simulation on the city of Innsbruck, Austria, serves as our ground-truth. • We utilize the COPERT IV model to estimate the emissions. • The results show the importance of the calibration of travel distances and network partitioning. • We propose a methodology based on the detour ratio to determine the travel distances. [ABSTRACT FROM AUTHOR]

• Short-sea shipping visibly contributes to particles concentrations in coastal areas. • The bottom-up model predicts consistent particle number concentration, PN, values. • Differently, contribution of ships on PM2.5 cannot be inferred by bottom-up model. • Existing regional fuel quality restrictions mostly reduce PM2.5 emissions. • Cleaner fuels and available after-treatment systems highly reduce PN/PM2.5 levels. Several studies indicate that short-sea shipping is an important source of air pollution for coastal areas and port cities. This paper reports results of a non-reactive particles dispersion model and a new set of experiments implemented for the Channel of Procida (Italy), an area with a high signal-to-noise ratio, due to intense marine traffic and low background pollution. The model successfully predicts particle number concentrations but underestimates PM 2.5 data. Model and experiments show that thanks to the EU policies on marine fuels, the Channel of Procida already has good air quality levels. Besides, the paper demonstrates that fostering the use of LNG or methanol or the application of an exhaust-gas-cleaning-system may allow reducing particles emissions well above 90%. The reliability of control strategies and the benefits for the population suggest that the introduction of regulations on particles emissions for ships can be a realistic option for the future environmental policy agenda. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) adoption in the U.S. will be accelerated by the historic $7.5 billion public investments in EV charging infrastructure. Careful analysis of EV charging demands plays a vital role in understanding the energy requirements, power grid impact, and smart charging management opportunities of EVs. To this end, this paper develops a data-driven trip-chaining-based modeling framework including five steps: Trip data acquisition and preprocessing, EV adoption modeling, travel itinerary synthesis, EV charging demand simulation and EV load profile generation. The developed analysis framework was demonstrated using real-world data for one region in Virginia, U.S. The results show that the proposed modeling framework can work effectively. For the study region in 2040, the predicted number of plug-in EVs is 470,114, resulting in a weekly charging demand of 38,078,127 kWh (55 % home, 9 % work, and 36 % public) in September and 45,920,358 kWh (61 % home, 9 % work, and 30 % public) in February. [ABSTRACT FROM AUTHOR]

Publicly developed logistics parks (PDLPs) have been considered one of the measures in urban logistics policies to reduce carbon emissions. In response, this paper draws on the "pollution transfer" hypothesis, constructs a carbon emission analysis framework for PDLPs, and uses spatial econometric methods to explore their carbon emission effects. The findings suggest that from a global perspective, PDLPs can lead to the emergence of "pollution havens" in the suburban and exurban areas while relieving the carbon emission burden in the urban core. Secondly, PDLPs can further contribute to forming "pollution havens" by promoting logistic re-agglomeration, and the "innovation compensation" effect of PDLPs is not significant. Finally, the carbon emission effects of PDLPs are spatiotemporally heterogeneous. A carbon reduction effect is noted when the logistic re-agglomeration in the location of PDLPs is higher, and an "innovation compensation" effect is also produced when the technological innovation is higher. [ABSTRACT FROM AUTHOR]

This paper aims to propose a novel Road Traffic Noise Model (RTNM), capable of dynamically assessing road traffic noise levels from reliable data (hourly traffic volumes and speed), supporting or replacing noise sensor networks, and addressing noise pollution concerns. RTNM is composed of two parts: i) the Vehicle Noise Specific Power model (for the assessment of the sound power level – L w of passenger cars, considering speed and motorization information) coupled with the CNOSSOS model (for the estimation of heavy-duty vehicles' L w); and ii) a sound propagation model (to evaluate noise levels at the receiver point). Inputs for the RTNM are retrieved from a radar installed in Aveiro city, Portugal, while the model estimations are validated by comparing them with levels recorded by a noise sensor installed close to the radar. It was found that the resulting noise estimations are robust, with associated mean absolute percentage errors not exceeding 5.8%. [ABSTRACT FROM AUTHOR]

• System thinking explores the interacting feedback loops of car dependency. • Transportation goals are achieved through dominating feedback loops. • Historical policies determine which feedback loop(s) dominate the system. • Road-based feedback loops dominate the transport system in a car-dependent city. • Appropriate timing and scale of policy intervention can shift the loop dominance. Despite decades of research on urban transportation, few researchers apply a holistic understanding of the urban transport mechanism. To address this gap, in this paper we employed a two-stage modeling approach using a system dynamics method and theory of path dependence. First, an exploratory model presents the structure, including feedback loops and underlying mechanisms of the evolution of car dependency. The model explores loop dominance, and implicit goals determine whether it is a car-dependent or transit-oriented and active modes-based transport system. Car dependence arises from the dominance of road-based feedback loops for commuters to achieve their transportation goals. Second, a revised policy structure reveals that shifting the loop dominance towards transit-oriented and active modes-based transportation system is possible when commuters achieve their goals through transit and active infrastructure-based feedback loops. The scale and timing of policy leverages determine the thresholds for the loop dominance shift. [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]

Despite noticeable improvements in electric vehicle (EV) technology, EV charging time remains high, and the lack of fast-charging infrastructure extends the travelling time for long-distance trips even further. Charging strategies to coordinate EVs' charging plans dynamically will help reduce station waiting times. This paper aims to quantify and compare the performances of two decentralised strategies using regular information-sharing between EVs and stations to estimate future waiting time in charging stations accurately. The communication strategy relies only on the communication of optimal charging plan computed by EVs to stations without any reservation. In contrast, the reservation strategy enables additionally the booking of optimal charging time slots. In a dedicated multi-agent simulation framework, we tested both strategies on different levels of infrastructure saturation. The communication strategy shows the best performance especially when combined with more frequent charging stops. • Two charging strategies are compared: one using communication, the other reservation. • Communication reduces by up to 12.8% the time spent in charging stations. • Multiplying stops and allowing charges above 80% of SoC improve both strategies. • Communication alone has better performance than the reservation. [ABSTRACT FROM AUTHOR]

To inform charger deployment decisions, this paper aims to understand the potential utilization and deployment priority for public charging infrastructure. A data-driven Cumulative Public Recharging (CPR) model is developed to explore the travel patterns by using 2017 National Household Travel Survey data. Given the daily trip sequence, trip distance, and dwell times, the study examines the daily expected driving range and BEV feasibility under different charging speeds, battery capacity, and charging behaviors. The results suggest that more advanced public chargers increase the daily expected driving range. Home charging is sufficient for most daily short-distance trips while public chargers are still needed for medium- and long-distance trips. Extreme fast charging (xFC) may not be necessary for people with home charging but could be more useful for people without home charging and for urgent charging. xFC becomes even less important to drivers with longer BEV ranges, a finding that contradicts conventional thinking. [ABSTRACT FROM AUTHOR]

Cycling benefits human health and helps to mitigate environmental issues. However, limited evidence exists regarding how the built environment influences cycling volume under different time and weather conditions. In this paper, we employed a Gradient Boosting Decision tree method to analyze the non-linear and threshold effects of the multiscale built environment and microclimate on cycling volume. Results based on the multisource data of The Netherlands show that 27 out of the 28 variables have a non-linear and threshold effect on cycling volume. Temperature is found to be a dominant factor among all variables. At street level, slope is the most important factor, followed by the green view and sky view indexes. At neighborhood level, population density is the most important factor, followed by residential density, and the density of bus stops. These findings offer useful insights for planning a cycling-friendly urban built environment at different scales. [ABSTRACT FROM AUTHOR]

Studies on travel satisfaction have proliferated recently. However, research efforts to conceptualize travel satisfaction are relatively scarce. One important issue is what reference points people use to evaluate travel satisfaction. While previous research considered travel preference as a reference point, people may compare travels to other reference points, such as travel experience and peers' travel. This paper aims to clarify the role of preferred, past, and peers' travels in travel satisfaction. Multi-group structural equation models are adopted to capture the heterogeneity of such effect across commuters by different transport modes. Household travel survey data collected in 2018 in Shanghai, China are used for modeling. We found that all three reference points are at play in evaluating travel satisfaction. Preferred and peers' travels matter more for commuters using motorized transport modes than those using non-motorized modes; travel experience matters less for commuters by public transport than those by other transport modes. [ABSTRACT FROM AUTHOR]

Due to the fundamental differences in motors and internal combustion engines, the real-time energy consumption profiles of internal combustion engine vehicles (ICEVs) and electric vehicles (EVs) are different, which motivates the need to identify the driving cycle for different types of vehicles. Existing EV driving cycle studies did not provide comparisons with ICEV driving cycles using the same geographical locations. This paper proposes a systematic method to develop the driving cycle cycles for EVs and ICEVs and combine the self-organizing map and support vector machine to eliminate the inconsistent clustering results in the driving segment classification, improving the clustering performance by 6.06–16.05%. Then, the driving cycles for the EV and ICEV are established under peak and off-peak traffic periods, and compared in the same traffic environment to illustrate the influence of driving cycle electrification. The emissions and energy consumption are also analyzed and compared for both types of vehicles. [ABSTRACT FROM AUTHOR]

Extreme rainstorms pose significant challenges to urban road network operations. This paper aims to propose a comprehensive framework to assess the resilience of urban road networks against rainstorm waterlogging disasters. We employ a scenario simulation method to analyze the impact of rainstorm waterlogging disasters on the road network and establish a resilience assessment framework based on both structural and functional performance. Within this framework, five distinct strategies are implemented to enhance road network resilience. The framework is applied to a case study of the downtown area of Xi'an, China. The results highlight the substantial impact of rainstorm intensity on urban road network resilience and suggest that analyzing critical road segments from the perspectives of importance and connectivity can significantly improve road network resilience. Notably, the arrangement of critical roads is pivotal in enhancing road network resilience. This research provides a theoretical reference for road network assessment and disaster reduction decision-making. [ABSTRACT FROM AUTHOR]

The number of machine learning applications to explore the complex relationship between land use and travel behavior has proliferated during the past several years. This discussion paper underscores the advantages and limitations of using machine learning approaches to reveal the complexity, compared to conventional parametric statistical models. We highlight the new insight derived from recent machine learning applications and call for further research to scrutinize the complex relationship and, especially, uncover the threshold association between land use and travel behavior. [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]

Understanding the driving behavior of multi-car households is crucial to evaluate the effectiveness of policies aimed at reducing fuel consumption in the passenger car fleet. In this paper, we investigate whether households adjust their vehicle miles traveled (VMT) among their cars in response to changes in fuel prices. We use data from the 2017 National Household Travel Survey (NHTS) on two-car households, where both cars are powered by gasoline, and estimate econometric models that distinguish cars based on their fuel economy. Our results show that an increase in per-mile driving cost significantly reduces the demand for driving the same car and increases demand for driving the other car, with little to no evidence of overall substitution at the daily or annual level. However, further investigation using artificial monthly travel diary data revealed a pronounced substitution towards the most fuel-efficient car only when there is a large and sustained increase in gas price. [ABSTRACT FROM AUTHOR]

The paper simulates the spatial variations in the sources of, and exposure to, traffic-related PM10 emissions for the city of Vienna, Austria. Using an extended and calibrated MATSim micro-simulation model, we reproduce agent-level mobility patterns for a representative day. Street-level PM10 emissions, mostly from cars, are extrapolated for the entire city to estimate concentration and exposure levels at hourly intervals. We show that exposure levels exceed the recommended 50 μ g/m 3 threshold between peak travel hours at home, education, and work locations. Among different socioeconomic status (SES) groups, urban, single, 15 years and younger, and those living near the city center face high exposure levels, while car users, that cause a majority of the emissions, are relatively less exposed. Finally, we show that Shared Autonomous Electric Vehicles (SAEVs) reduce PM10 emissions, but the benefits are not homogeneously distributed across the different SES groups. [ABSTRACT FROM AUTHOR]

The paper explores how governing bodies and planning authorities in Norway take urban freight transport into consideration in three different cities. Based on empirical studies of actors and processes relevant to city planning, the paper highlights challenges related to integrating urban freight transport considerations in city planning. The paper demonstrates how different planning approaches shape the integration of urban freight transport in city planning. The paper shows that early integration of freight considerations and stakeholder engagement in city planning is vital for developing more effective and sustainable transport and freight systems in urban environments. Political anchorage, geographical scope, and time are also three dimensions that considerably influence the way urban freight transport is integrated in city planning. Insights from this analysis may be used to develop better ways of integrating freight transport into city planning in the future. [ABSTRACT FROM AUTHOR]

This paper analyses the effectiveness of self-evacuation activities of population by private vehicle transport from flood hazard areas, aimed at minimising the negative effects of flooding.. The paper relies on a four-step traffic model which is based, inter alia, on the results of questionnaire studies. Moreover, the model takes into account the entirety of national traffic, which allows the methodological problems related to the border effect to be overcome. As shown in the study, the shortest or the fastest routes achievable in the pre-flood period are not always most optimal when the flood has already occurred. In such a case, evacuation planning will increase the efficiency of the process. Thus, inadequate designation of evacuation routes may adversely affect the process of relocating people to places of safety. Therefore, it is important to create plans that provide information on evacuation zones, routes and destinations. [ABSTRACT FROM AUTHOR]

With the rapid growth of rural cars ownership, the environmental pollution caused by rural traffic has become a new problem restricting the sustainable development of social economy. Therefore, encouraging and supporting rural residents' green travel has become the focus of government and academic circles. Based on the context of China's local rural social culture, by adopting the secondary data from the China Land Economics Survey included 2600 farmers in 52 Administrative Villages from 13 prefecture-level cities in Jiangsu Province, this paper examines the impacts of social influence metrics and the moderation effects of social circle and similarity on the individual's green travel behavior in rural areas in China. The results show that the significant and different impacts of social influence metrics. Significant and positive impact exist in the social influence from the neighbors who adopt the green travel behavior, while significant and negative impact also exist in the social influence from the neighbors who adopt the non-green travel behavior. Moreover, we also find the significant moderators including the social circle and similarity between the target family and the neighbors who adopt green or non-green travel behavior. This paper has important theoretical and practical significance for enriching and developing the relevant theories of green travel. [ABSTRACT FROM AUTHOR]

[Display omitted] Pavement sustainability is measured using various methodologies which often focus on only certain aspects of sustainability. Methods to quantify and unify holistic sustainability in terms of economic, environmental and social consequences are lacking. In previous papers, the major findings of the contribution of construction, maintenance and use to pavement sustainability were presented. The objective of this paper is to present a method of quantification using a risk and sustainability index that can compare the design and maintenance options of pavement systems. The model utilises Markov chain Monte Carlo simulations applied to a conceptualised influence diagram to determine the probability of sustainability using a cumulative approach. Previously reported results are provided which form the basis of the model, detailing economic, environmental and social results of pavement alternatives, followed by the development of a probability model to quantify holistic pavement sustainability. In conclusion, even though sustainability is complex, simplification through simulation is achievable. [ABSTRACT FROM AUTHOR]

• Energy consumption of eight car and bus technologies are modelled (450 simulations) • Powertrains include conventional, hybrid, electric, and fuel cell electric. • Car-share, ride-share, private, and bus service modes WTW trip-emissions are estimated. • Local operating contexts sway the environmental benefit of a mobility solution. • Vehicle occupancy critically impacts passenger-trip-level environmental benefit. • Occupancy thresholds for technology/service mode are defined. This paper estimates the environmental impact of alternative and conventional transportation technologies across the dimensions of service mode and power source pathway. We simulate the Well-to-Wheel energy consumption and GHG emissions of eight transit buses and passenger car powertrains. Vehicles are simulated under three generalized North American operating contexts (450 operating scenarios) using Autonomie and the GREET database. All technologies are normalized by passenger-service-mode-trip-km-travelled GHG emissions to facilitate equivalent comparison. The results indicate that all simulated mobility solutions carry a large variability; however, the most environmentally competitive solutions are fuel cell electric car-share, battery electric car-share, and battery-electric bus, all powered by low-carbon intensity power sources at average occupancy (0.23–19.7 g CO 2 e passenger-service-mode-trip-km-travelled-1). Furthermore, transit bus technologies have the potential to reduce up to 2.3 times more GHG per passenger-trip than comparable ride-share technologies. Overall, this paper defines occupancy GHG emission thresholds for mobility solutions to inform environmental decision-making processes. [ABSTRACT FROM AUTHOR]

• We explore the agency for energy efficiency in all major types of ship operations. • How do voyage planning and execution decisions affect energy efficiency? • Commercial decisions matter more for energy efficiency than operational decisions. • Networked agency for energy efficiency limits climate change mitigation potential. • Policymakers should expand regulatory focus to cargo owners to reduce emissions. To mitigate climate change due to international shipping, the International Maritime Organization (IMO) requires shipowners and ship technical managers to improve the energy efficiency of ships' operations. This paper studies how voyage planning and execution decisions affect energy efficiency and distinguishes between the commercial and nautical components of energy efficiency. Commercial decisions for voyage planning depend on dynamic market conditions and matter more for energy efficiency than nautical decisions do for voyage execution. The paper identifies the people involved in decision-making processes and advances the energy-efficiency literature by revealing the highly networked nature of agency for energy efficiency. The IMO's current energy efficiency regulations fail to distinguish between the commercial and nautical aspects of energy efficiency, which limits the ability to mitigate climate change through regulatory measures. Policymakers should expand their regulatory focus beyond shipowners and technical managers to cargo owners to improve energy efficiency and reduce maritime transport emissions. [ABSTRACT FROM AUTHOR]