The problem of cold starts: A closer look at mobile source emissions levels

While the phenomenon of excess vehicle emissions from cold-start conditions is well known, the magnitude and duration of this phenomenon is often unclear due to the complex chemical processes involved and uncertainty in the literature on this subject. This paper synthesizes key findings regarding the influence of ambient and engine temperatures on light-duty vehicle (LDV) emissions. Existing literature, as well as analytical tools like the U.S. Environmental Protection Agency’s Motor Vehicle Emission Simulator (MOVES), indicate that while total vehicle emissions have dropped significantly in recent years, those associated with cold starts can still constitute up to 80% for some pollutant species. Starting emissions are consistently found to make up a high proportion of total transportation-related methane (CH₄), nitrous oxide (N₂O), and volatile organic compounds (VOCs). After 3–4 min of vehicle operation, both the engine coolant and the catalytic converter have generally warmed, and emissions are significantly lower. This effect lasts roughly 45 min after the engine is shut off, though the cooling rate depends greatly on the emission species and ambient temperature. Electrically (pre-)heated catalysts, using the bigger batteries available on hybrid drivetrains and plug-in vehicles, may be the most cost-effective technology to bring down a sizable share of mobile source emissions. Trip chaining (to keep engines warm) and shifting to non-motorized modes for shorter trips, where the cold start can dominate emissions, are also valuable tactics.     

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.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.     

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。     

基于沉降差的填石路堤施工工艺与质量控制研究

结合南方地区填石路堤施工,通过填石路堤试验段研究,介绍了填石路堤的施工工艺和质量控制要求,并通过沉降差检测分析,说明了沉降差作为填石路堤质量控制指标的可行性,为同类工程提供参考.     

公路沥青混凝土路面施工质量控制措施探析

沥青是我国用于公路路面铺设的典型材料.对沥青混凝土路面施工质量控制进行分析,并提出相应的施工质量控制措施,为施工企业提供借鉴.     

加强教风学风建设 不断提高人才培养质量

在改革不断深入、经济社会深度转型的当下,大学生群体呈现出新的特点和个性。在新的形势下,要加强高校教风学风建设,更好的发挥高校培养人才的作用,促使人才培养质量提升。本文以辽宁省交通高等专科学校为例,着重从文化建设、教师育人能力提升、学生职业梦想等角度入手,提出了加强教风学风建设的具体举措和途径。