Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Did Chinese cities that implemented driving restrictions see reductions in PM10?

Imposing driving restrictions is becoming increasingly popular as a policy intended to control urban air pollution. Existing studies on this topic offer highly mixed observations, and each study tends to focus on only one city. In this paper, we used 11 Chinese cities with driving restrictions as the treatment group, and compared them to other cities that did not implement the policy. Based on a propensity score matching and difference-in-difference analysis, we found no evidence of a decrease in PM10 concentrations in cities after they implemented driving restrictions. This finding may be attributed to an increase in the number of cars in these cities after implementing driving restrictions, but we also found no evidence of an improvement in air quality for a given number of cars after implementation of the policies.     

Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO₂) concentrations as the effect observed on nitrogen oxide (NO_x) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO₂ levels increased between 0.1% and 10% with respect to the base-case while changes in NO_x emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO₂ concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO₂ levels.     

Validating and improving public transport origin–destination estimation algorithm using smart card fare data

Smart card data are increasingly used for transit network planning, passengers’ behaviour analysis and network demand forecasting. Public transport origin–destination (O–D) estimation is a significant product of processing smart card data. In recent years, various O–D estimation methods using the trip-chaining approach have attracted much attention from both researchers and practitioners. However, the validity of these estimation methods has not been extensively investigated. This is mainly because these datasets usually lack data about passengers’ alighting, as passengers are often required to tap their smart cards only when boarding a public transport service. Thus, this paper has two main objectives. First, the paper reports on the implementation and validation of the existing O–D estimation method using the unique smart card dataset of the South-East Queensland public transport network which includes data on both boarding stops and alighting stops. Second, the paper improves the O–D estimation algorithm and empirically examines these improvements, relying on this unique dataset. The evaluation of the last destination assumption of the trip-chaining method shows a significant negative impact on the matching results of the differences between actual boarding/alighting times and the public transport schedules. The proposed changes to the algorithm improve the average distance between the actual and estimated alighting stops, as this distance is reduced from 806 m using the original algorithm to 530 m after applying the suggested improvements.     

Integrated Transport System of the South-Moravian Region and its impact on rural development

It is generally presupposed that the infrastructure and availability of services of general interest (like schools, medical care, social services and also public transport) impact on present demographic development in rural areas, namely depopulation and aging. Such services affect the quality of life of local people and sometimes they perform a vital necessity. It is possible to say that the absence of the mentioned services should be compensated by an effective system of public transport. In other case, especially those people who are not able to use individual cars due to the age, health, legal conditions or financial situation are bequeathed on an assistance of the family or neighbors or they stay cut off and excluded. This paper is aimed at the verification of the presupposition in the case of the South-Moravian Region – NUTS 3 region occupying the south-eastern part of the Czech Republic, bordering with Austria and Slovakia. The research method lies in analysis of the frequency, travel time and fare of public transport system and its comparison with demographic development in rural areas, especially in the peripheral ones. The results are discussed in view of the system of central places in the region and present urbanization processes like suburbanization, counterurbanization and reurbanization.     

Happy or liberal? Making sense of behavior in transport policy design

Appropriate microeconomic foundations of mobility are decisive for successful policy design in transportation and, in particular, for the challenge of climate change mitigation. Recent research suggests that behavior in transportation cannot be adequately represented by the standard approach of revealed preferences. Moreover, mobility choices are influenced by factors widely regarded as normatively irrelevant. Here we draw on insights from behavioral economics, psychology and welfare theory to examine how transport users make mobility decisions and when it is desirable to modify them through policy interventions. First, we explore systematically which preferences, heuristics and decision processes are relevant for mobility-specific behavior, such as mode choice. We highlight the influence of infrastructure on the formation of travel preferences. Second, we argue that the behavioral account of decision-making requires policy-makers to take a position on whether transport policies should be justified by appealing to preference satisfaction or to raising subjective well-being. This distinction matters because of the (i) influence of infrastructure on preference formation, (ii) health benefits from non-motorized mobility, (iii) negative impact of commuting on happiness and (iv) status-seeking behavior of individuals. The orthodox approach of only internalizing externalities is insufficient because it does not allow for the evaluation of these effects. Instead, our analysis suggests that transport demand modeling should consider behavioral effects explicitly.     

Technical and environmental effects of biodiesel use in local public transport

Biodiesel use in local public transport could be especially significant in improving air quality in cities. The purpose of the experiments described in this paper was to evaluate the various (10, 20 and 50%) blends of biodiesel with diesel in the context of the engine and pollution aspects. As regards the experimental use of these findings on municipal buses, these experiments were the first reference in Hungary. The ages (15–20 years) and types of buses (Ikarus-280, Ikarus-260) used in the experiments are still common vehicles in Hungarian public transport. During our measurements, there was a significant difference between the change in fuel consumption of articulated and solo buses in traffic when compared to test bench measurements. The proportion of the engine performance reduction is nearly the same as that for biodiesel share in the blends. Most pollutants were decreasing (both at idle and full rpm), but this reduction is not directly proportional to the increase of the blending percentage. However, as for CO₂, emission increase was observed in the case of idle rpm in comparison to normal diesel operation, even though this phenomenon was not due to biodiesel use, but the catalytic converter and the fact that biodiesel was used for the first time in the engine concerned.     

高速公路沥青路面施工质量控制分析

无接缝、平整、行车舒适、噪音低以及振动小、易于养护等优点,使沥青混凝土路面成为我国国内公路面层普遍采用的一种比较好的结构形式。但是如果施工中不能按照施工工艺严格的进行施工质量控制,则很容易导致路面的一系列质量问题,这不仅影响使用功能,还影响影响其社会效益。     

关于大学生心理健康教育课程的几点思考

大学生心理健康教育课程教学的目的是培养学生健康的心理和良好的心理素质,使其在思想认识、知识和技能三个层面学有所获。课程教学应遵循理论与实践相结合、教师讲授与学生体验相结合,通过课堂讲授、小组讨论与典型案例分析、心理素质训练与拓展等体验式教育方法进行教学;采用理论效果评估与实际操作效果评估相结合的方式对课程效果进行评估。