A forecast air pollution model applied to a hypothetical urban road pricing scheme: An empirical study in Madrid

Reducing the air pollution from increases in traffic congestion in large cities and their surroundings is an important problem that requires changes in travel behavior. Road pricing is an effective tool for reducing air pollution, as reflected currently urban road pricing outcomes (Singapore, London, Stockholm and Milan). A survey was conducted based on establishing a hypothetical urban road pricing system in Madrid (a random sample size n = 1298). We developed a forecast air pollution model with time series analysis to evaluate the consequences of possible air pollution decreases in Madrid. Results reveal that the hypothetical road pricing for Madrid could have highly significant effects on decreasing air pollution outside of the city and in the inner city during the peak operating time periods of maximum congestion (morning peak hours from 7:00 to 10:00 and evening peak hours from 18:00 to 20:00). Furthermore, this system could have significant positive effects on a shift toward using public transport and non-motorized modes inside the hypothetical toll zone. This reveals that the system has a high capacity to motivate a decrease in air pollution and impose more sustainable behavior for public transport users.     

Traffic control oriented impact on the persistence of urban air pollutants: A causeway bay revelation during emergency period

The continuous traffic flow is always considered to take a great extent responsibility for the air quality deterioration in urban areas. Meanwhile, traffic control is assumed to be one of the most effective ways to mitigate the high concentration situation as this may cut off the emission directly and satisfy the air quality objectives. Unfortunately, the overdevelopment of central business district area in megacities not only complicates the control plan, but also troubles the process of plan assessment. Because of the road blockages caused by the radical behavior during the Hong Kong protest in 2014, it offers an unexpected chance to evaluate the influence of traffic control oriented plan on urban (i.e., Causeway Bay) air pollution. Hence, we here investigated the six air pollutants concentrations that measured in the time series before, during and after the Hong Kong Protest period. The impact of traffic flow restriction on pollutants’ persistence has been quantified both qualitatively and quantitatively in this study. The results showed that the persistence of pollutants was a general property in Causeway Bay which dominated by the traffic flow pattern. The road blockages, considered as one kind of extreme traffic control plan, would strengthen the persistence of most pollutants (except ozone). Moreover, it also indicated that comprehensive consideration and further balance among different pollutants were necessary when try to reduce pollution in urban area by traffic control.     

How to best address aviation’s full climate impact from an economic policy point of view? – Main results from AviClim research project

The interdisciplinary research project AviClim (Including Aviation in International Protocols for Climate Protection) has explored the feasibility for including aviation’s full climate impact, i.e., both long-lived CO₂ and short-lived non-CO₂ effects, in international protocols for climate protection and has investigated the economic impacts. Short-lived non-CO₂ effects of aviation are NO_x emissions, H₂O emissions or contrail cirrus, for instance.Four geopolitical scenarios have been designed which differ concerning the level of international support for climate protecting measures. These scenarios have been combined alternatively with an emissions trading scheme on CO₂ and non-CO₂ species, a climate tax and a NO_x emission charge combined with CO₂ trading and operational measures (such as lower flight altitudes). Modelling results indicate that a global emissions trading scheme for both CO₂ and non-CO₂ emissions would be the best solution from an economic and environmental point of view. Costs and impacts on competition could be kept at a relatively moderate level and effects on employment are moderate, too. At the same time, environmental benefits are noticeable.     

The significant impacts on traffic and emissions of ferrying children to school in Beijing

After having implemented numerous regulations, e.g., coercive policies on vehicle use and purchase, it is becoming increasingly difficult to find further potential to control vehicle emissions in Beijing, as the air quality is still poor. This research provides a different approach for policy-makers to reduce vehicle emissions by managing demand. We found that parents ferrying their children to and from school is an important but long-neglected contributor to traffic congestion and vehicle emissions. This phenomenon is very common in China because of the social culture. In this research, parallel tests during both the school season and the non-school season were adopted, and emissions in both seasons were calculated based on travel demand and emission models. The results revealed that emissions factors (in g/km) for criteria pollutants and CO₂ increased by over 10% during rush hours during the school season due to traffic condition deterioration compared with non-school season. Daily HC, CO, NO_x, PM and CO₂ emissions from the passenger car fleet were 8.3%, 7.8%, 6.4%, 6.3% and 6.5% higher compared with those during the non-school season, respectively. These differences are greater than the total vehicular emission reduction by other control measures in 2014 in Beijing. For policy makers, providing safe and efficient ways to ferry children would be a useful and harmonious strategy for future vehicle emission control.     

SMART: simulation model for activities, resources and travel

This paper proposes the development of an activity-based model of travel that integrates household activities, land use patterns, traffic flows, and regional demographics. The model is intended as a replacement of the traditional Urban Transportation Planning System (UTPS) modeling system now in common use. Operating in a geographic-information system (GIS) environment, the model's heart is a Household Activity Simulator that determines the locations and travel patterns of household members daily activities in 3 categories: mandatory, flexible, and optional. The system produces traffic volumes on streets and land use intensity patterns, as well as typical travel outputs. The model is particularly well suited to analyzing issues related to the Clean Air Act and the Intermodal Surface Transportation Efficiency Act (ISTEA). Implementation would, ideally, require an activity-based travel diary, but can be done with standard house-interview travel surveys. An implementation effort consisting of validation research in parallel with concurrent model programming is recommended.     

化学耗氧量无汞快速测定法的研究

在原标准回流滴定法的基础上提出了化学耗氧量（ＣＯＤ）无汞快速测定法，同时采用银—氨络合还原法对化学耗氧量测定废液中的银进行了回收。采用本方法将一次测定ＣＯＤ的时间由原来的３ｈ缩短至１ｈ，精密度实验的相对标准偏差在±４％之内，加标回收率达到９８％以上，可以满足环境监测规定的要求。     

An application of activity-based travel analysis to simulation of change in behaviour

People are liable to exaggerate their future use of new transport facilities when they are interviewed about it before it is in operation. This is often due to the fact that they have no real frame of reference for the study. In order to overcome this, we have tried to perfect an original behaviour-change simulation method (Section 1). It has been tested on a town on the outskirts of Lyons (France) and has provided interesting results. However, to use it as a forecasting tool, we have to make sure that the assertions by potential users when interviewed are consistent with actual behaviour when the new facilities become available (Section 2). This test was carried out when a new light rail line was introduced in Grenoble (France). A first survey was undertaken before the opening of the new line, and people's actual (new) behaviour was surveyed after the new line opened. It is therefore possible to analyse the validity of the simulation (Section 3).     

谈空气滤清器对内燃机使用寿命的影响及拟解决方法

从内燃机使用过程中的经济性、可靠性、排污量与使用寿命之间的关系入手，简析颗粒磨损对内燃机使用寿命的影响；指出了国产内燃机空气滤清器使用中存在的问题，提出了适合中国国情的空气滤清器的使用、更换及鉴别方法。     

An investigation of the reliability of real-time information for route choice decisions in a congested traffic system

This paper investigates the reliability of information on prevailing trip times on the links of a network as a basis for route choice decisions by individual drivers. It considers a type of information strategy in which no attempt is made by some central controller or coordinating entity to predict what the travel times on each link would be by the time it is reached by a driver that is presently at a given location. A specially modified model combining traffic simulation and path assignment capabilities is used to analyze the reliability of the real-time information supplied to the drivers. This is accomplished by comparing the supplied travel times (at the link and path levels) to the actual trip times experienced in the network after the information has been given. In addition, the quality of the decisions made by drivers on the basis of this information (under alternative path switching rules) is evaluated ex-post by comparing the actually experienced travel time (given the decision made) to the time that the driver would have experienced without the real-time information. Results of a series of simulation experiments under recurrent congestion conditions are discussed, illustrating the interactions between information reliability and user response.     

Calibrating aggregate travel demand models with traffic counts: Estimators and statistical performance

Traffic counts on network links constitute an information source on travel demand which is easy to collect, cheap and repeatable. Many models proposed in recent years deal with the use of traffic counts to estimate Origin/Destination (O/D) trip matrices under different assumptions on the type of "a-priori" information available on the demand (surveys, outdated estimates, models, etc.) and the type of network and assignment mapping (see Cascetta & Nguyen 1988). Less attention has been paid to the possibility of using traffic counts to estimate the parameters of demand models. In this case most of the proposed methods are relative to particular demand model structures (e.g. gravity-type) and the statistical analysis of estimator performance is not thoroughly carried out. In this paper a general statistical framework defining Maximum Likelihood, Non Linear Generalized Least Squares (NGLS) and Bayes estimators of aggregated demand model parameters combining counts-based information with other sources (sample or a priori estimates) is proposed first, thus extending and generalizing previous work by the authors (Cascetta & Russo 1992). Subsequently a solution algorithm of the projected-gradient type is proposed for the NGLS estimator given its convenient theoretical and computational properties. The algorithm is based on a combination of analytical/numerical derivates in order to make the estimator applicable to general demand models. Statistical performances of the proposed estimators are evaluated on a small test network through a Monte Carlo method by repeatedly sampling "starting estimates" of the (known) parameters of a generation/distribution/modal split/assignment system of models. Tests were carried out assuming different levels of "quality" of starting estimates and numbers of available counts. Finally NGLS estimator was applied to the calibration of the described model system on the network of a real medium-size Italian town using real counts with very satisfactory results in terms of both parameter values and counted flows reproduction.