Air quality impacts of electric vehicle adoption in Texas

Widespread adoption of plug-in electric vehicles (PEVs) may substantially reduce emissions of greenhouse gases while improving regional air quality and increasing energy security. However, outcomes depend heavily on the electricity generation process, power plant locations, and vehicle use decisions. This paper provides a clear methodology for predicting PEV emissions impacts by anticipating battery-charging decisions and power plant energy sources across Texas. Life-cycle impacts of vehicle production and use and Texans’ exposure to emissions are also computed and monetized. This study reveals to what extent PEVs are more environmentally friendly, for most pollutant species, than conventional passenger cars in Texas, after recognizing the emissions and energy impacts of battery provision and other manufacturing processes. Results indicate that PEVs on today’s grid can reduce GHGs, NO_x, PM₁₀, and CO in urban areas, but generate significantly higher emissions of SO₂ than existing light-duty vehicles. Use of coal for electricity production is a primary concern for PEV growth, but the energy security benefits of electrified vehicle-miles endure. As conventional vehicle emissions rates improve, it appears that power grids must follow suit (by improving emissions technologies and/or shifting toward cleaner generation sources) to compete on an emissions-monetized basis with conventional vehicles in many locations. Moreover, while PEV pollution impacts may shift to more remote (power plant) locations, dense urban populations remain most strongly affected by local power plant emissions in many Texas locations.     

The impact of Gulf carrier competition on U.S. airlines

Gulf carriers, such as Emirates Airline, Etihad Airways, and Qatar Airways, have expanded aggressively and are creating an increasingly dense global network. These carriers’ future growth prospects, however, hinge on their ability to gain access to markets in Europe and America, for example. Existing bilateral agreements stifle the Gulf carriers’ ambitious expansion plans in some instances, and incumbent carriers lobby to restrict further market access. To contribute to this debate, the objective of this research is to empirically examine the effects of Gulf carrier competition on U.S. carriers’ passenger volumes and fares in international route markets. Based on data obtained from the U.S. Department of Transportation, the empirical results suggest that greater competition by Gulf carriers in U.S. international markets is associated with (1) significant growth in U.S.–Middle East traffic volumes and (2) small but statistically significant traffic losses and fare reductions for U.S. carriers in route markets connecting the U.S. with Africa, Asia, Australia and Europe.     

模糊需求下快捷货物低碳运输方式及路径选择

针对模糊需求下的低碳快捷货运运输方式选择及路径规划问题,运用模糊优化理论,以2-型三角模糊变量表示不确定需求,以运输成本和碳排放量为目标,建立多目标模糊机会约束规划模型。采用逼近理想解排序法对多目标进行处理,得出不同置信水平下的快捷货物运输方案;进而探讨置信参数变化时对运输成本及碳排放量的影响,分析运输成本及碳排放量随运输时间的变化情况。研究结果表明:碳排放量对快捷货物运输方式及路径选择具有一定影响;需求不确定时,在满足运到时限的前提下,合理选择运输方式和路径对于降低运输成本和减少碳排放具有重要意义。     

考虑偏好差异的后疫情时代居民出行方式选择行为研究

为探究后疫情时代居民出行方式选择行为，运用选择实验的方法，基于问卷调查获得选择行为数据，构建出行方式选择的混合Logit模型和潜在类别条件Logit模型。采用Stata软件标定模型参数，得到后疫情时代影响居民出行方式选择的主要因素。结果表明，两种模型均体现了个体出行方式选择的异质性，潜在类别条件Logit模型与混合Logit模型相比拟合优度提高了13%， 预测精度提高了3.03%，为突发公共卫生事件下分析出行行为的个体异质性提供了一种有效工具。潜在类别条件Logit模型根据居民所处低、中风险区两种情景，分别将居民划分为4类、5类人 群。从出行方式属性上看，等待时间和在途时间成为居民选择出行方式最重要的影响因素。从个人社会经济属性上看，在后疫情时代收入更高的女性更倾向选择私家车出行，年龄越大对行程费用越敏感，男性更愿意选择公交、地铁出行。     

Travel,transport and energy implications of university-related student travel: A case study approach

This study highlighted significant cultural differences and complexity in travel behaviour associated with travel to university across the UK and Ireland. This paper examines university travel behaviours and the implications for emissions, across the 2012–2013 academic year, based on responses from 1049 students across 17 universities in Ireland and the UK. Surveys were analysed to examine the trips of students both during term time and when accessing the universities each year. The data analysis in this paper examines three aspects of the transport implications of travel to and from university. Firstly the journey between university and term time address (or permanent address if the respondent does not have a separate term time address), secondly the journey between the university area and a separate permanent address where relevant; and thirdly implications for emissions resulting from university-related travel.The study found that student car users were more likely to be female, older students, or studying part time; male students were more likely to use active modes. The study indicated interesting differences between students living in different parts of the UK and Ireland. For example, it was found that there was a higher level of car dependence amongst Northern Irish students compared to other areas; and a greater variability in travel distances in Scotland and Northern Ireland. In England, car use was more pronounced when students travelled from their permanent address to term time address, and, as in Ireland, there was evidence of more car sharing on such trips. Public transport usage was more pronounced amongst Scottish students. The effect of these transport choices on emissions is significant and demonstrates the importance of education related trips to the development of a transport policy response. The analysis shows that annual emissions are highest for regular travel to and from university when a student has a permanent address rather than a separate term time and permanent address.     

Urban delivery industry response to cordon pricing, time-distance pricing, and carrier-receiver policies in competitive markets

The paper develops a set of analytical formulations to study the behavior of the urban delivery industry in response to cordon time-of-day pricing, time-distance pricing, and comprehensive financial policies targeting carriers and receivers. This is accomplished by modeling the behavior of receivers in response to financial incentives, and the ensuing behavior of the carrier in response to both pricing and the receivers’ decisions concerning off-hour deliveries. The analytical formulations consider both the base case condition, and a mixed operation with both regular hour and off-hour deliveries; two pricing schemes: cordon time of day, and time-distance pricing; two types of operations: single-tour, and multi-tour carriers; and three different scenarios in terms of profitability of the carrier operation, which include an approximation to the best case, the expected value, and the worst case. The analyses, both theoretical and numerical, highlight the limitations of pricing-only approaches. In the case of cordon time of day pricing, the chief conclusion is that it is of limited use as a freight demand management tool because: (1) in a competitive market the cordon toll cannot be transferred to the receivers as it is a fixed cost and (2) the structure of the cost function, that only provides an incentive to the carrier to switch to the off-hours when all the receivers in the tour switch to the off-hours. The analyses of time-distance pricing clearly indicate that, though its tolls could be transferred to the receivers and provide an incentive for behavior change, the magnitude of the expected toll transfers under real life conditions are too small to have any meaningful impact on receivers choice of delivery times. In essence, the key policy implication is that in order to change the joint behavior of carrier and receivers, financial incentives—or programs that foster unassisted off-hour deliveries—should be made available to receivers in exchange for their commitment to do off-hour deliveries. As the paper proves, if a meaningful number of receivers switch to the off-hours, the carriers are likely to follow suit.     

基于广西旅游业的道路客运发展探析

文章针对广西道路旅客运输的现状及广西道路客运企业发展旅游业的优越条件,以＂运游结合＂为切入点,介绍以快捷优质的客运服务带动＂慢旅游＂道路客运企业发展旅游业的新模式,对采取＂运游结合＂经营模式,提高服务质量,发展＂慢旅游＂提出了相关的建议。     

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21%, 33%, 24% and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than non-commercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity.     

Weather impact on containership routing in closed seas: A chance-constraint optimization approach

Weather conditions have a strong effect on the operation of vessels and unavoidably influence total time at sea and associated transportation costs. The velocity and direction of the wind in particular may considerably affect travel speed of vessels and therefore the reliability of scheduled maritime services. This paper considers weather effects in containership routing; a stochastic model is developed for determining optimal routes for a homogeneous fleet performing pick-ups and deliveries of containers between a hub and several spoke ports, while incorporating travel time uncertainties attributed to the weather. The problem is originally formulated as a chance-constrained variant of the vehicle routing problem with simultaneous pick-ups and deliveries and time constraints and solved using a genetic algorithm. The model is implemented to a network of island ports of the Aegean Sea. Results on the application of algorithm reveal that a small fleet is sufficient enough to serve network’s islands, under the influence of minor delays. A sensitivity analysis based on alternative scenarios in the problem’s parameters, leads to encouraging conclusions with respect to the efficiency and robustness of the algorithm.