Concentration and oxidative potential of on-road particle emissions and their relationship with traffic composition : Relevance to exposure assessment

Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

A safety adapted car following model for traffic safety studies

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

Exploring perceived legitimacy of traffic law enforcement

The purpose of traffic law enforcement is to encourage compliant driver behaviour. That is, the threat of an undesirable sanction encourages drivers to comply with traffic laws. However, not all traffic law violations are considered equal. For example, while drink driving is generally seen as socially unacceptable, behaviours such as speeding are arguably less so, and speed enforcement is often portrayed in the popular media as a means of “revenue raising”. The perceived legitimacy of traffic law enforcement has received limited research attention to date. Perceived legitimacy of traffic law enforcement may influence (or be influenced by) attitudes toward illegal driving behaviours, and both of these factors are likely to influence on-road driving behaviour. This study aimed to explore attitudes toward a number of illegal driving behaviours and traffic law enforcement approaches that typically target these behaviours using self-reported data from a large sample of drivers. The results of this research can be used to inform further research in this area, as well as the content of public education and advertising campaigns designed to influence attitudes toward illegal driving behaviours and perceived legitimacy of traffic law enforcement.

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

Relating vehicle generated pollutants to urban stormwater quality

Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.

Navigational Safety in Port Waters : Proactive Management of Collision Risk Using Traffic Conflicts

Traditionally navigational safety analyses rely on historical collision data which is often hampered because of low collision counts, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these problems is using navigational traffic conflicts or near-misses as an alternative to the collision data. This book discusses how traffic conflicts can effectively be used in modeling of port water collision risks. Techniques for measuring and predicting collision risks in fairways, intersections, and anchorages are discussed by utilizing advanced statistical models. Risk measurement models, which quantitatively measure collision risks in waterways, are discussed. To predict risks, a hierarchical statistical modeling technique is discussed which identifies the factors influencing the risks. The modeling techniques are illustrated for Singapore port data. Results showed that traffic conflicts are an ethically appealing alternative to collision data for fast, reliable and effective safety assessment, thus possessing great potential for managing collision risks in port waters.

A new approach for trip generation estimation for use in traffic impact assessments

Findings from an online survey conducted by Queensland University of Technology (QUT) shows that Australia is suffering from a lack of data reflecting trip generation for use in Traffic Impact Assessments (TIAs). Current independent variables for trip generation estimation are not able to create robust outcomes as well. It is also challenging to account for the impact of the new development on public and active transport as well as the effect of trip chaining behaviour in Australian TIA studies. With this background in mind, research is being implemented by QUT to find a new approach developing a combined model of trip generation and mode choice with consideration of trip chaining effects. It is expected that the model will provide transferable outcomes as it is developed based on socio-demographic parameters. Child Care Centres within the Brisbane area have been nominated for model development. At the time, the project is in the data collection phase. Findings from the pilot survey associated with capturing trip chaining and mode choice information reveal that applying questionnaire is able to capture required information in an acceptable level. The result also reveals that several centres within an area should be surveyed in order to provide sufficient data for trip chaining and modal split analysis.

Integrating driving and traffic simulators to study railway level crossing safety interventions : a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost $10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers are particularly promising to improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs , driver distraction and workload when using the technology . Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road network featuring RLX for different market penetrations using a traffic simulation. This methodology can assist in evaluating future safety interventions at RLXs.

Varenicline decreases alcohol consumption in heavy-drinking smokers

Rationale Emerging evidence suggests that the α4β2 form of the nicotinic acetylcholine receptor (nAChR) modulates the rewarding effects of alcohol. The nAChR α4β2 subunit partial agonist varenicline (Chantix™), which is approved by the Food and Drug Administration for smoking cessation, also decreases ethanol consumption in rodents (Steensland et al., Proc Natl Acad Sci U S A 104:12518–12523, 2007) and in human laboratory and open-label studies (Fucito et al., Psychopharmacology (Berl) 215:655–663, 2011; McKee et al., Biol Psychiatry 66:185–190 2009). Objectives We present a randomized, double-blind, 16-week study in heavy-drinking smokers (n = 64 randomized to treatment) who were seeking treatment for their smoking. The study was designed to determine the effects of varenicline on alcohol craving and consumption. Outcome measures included number of alcoholic drinks per week, cigarettes per week, amount of alcohol craving per week, cumulative cigarettes and alcoholic drinks consumed during the treatment period, number of abstinent days, and weekly percentage of positive ethyl glucuronide and cotinine screens. Results Varenicline significantly decreases alcohol consumption (χ 2 = 35.32, p < 0.0001) in smokers. Although varenicline has previously been associated with suicidality and depression, side effects were low in this study and declined over time in the varenicline treatment group. Conclusions Varenicline can produce a sustained decrease in alcohol consumption in individuals who also smoke. Further studies are warranted to assess varenicline efficacy in treatment-seeking alcohol abusers who do not smoke and to ascertain the relationship between varenicline effects on smoking and drinking.

Adsorption of heavy metals by road deposited solids

The research study discussed in the paper investigated the adsorption/desorption behaviour of heavy metals commonly deposited on urban road surfaces, namely, Zn, Cu, Cr and Pb for different particle size ranges of solids. The study outcomes, based on field studies and batch experiments confirmed that road deposited solids particles contain a significantly high amount of vacant charge sites with the potential to adsorb additional heavy metals. Kinetic study and adsorption experiments indicated that Cr is the most preferred metal element to associate with solids due to the relatively high electro negativity and high charge density of trivalent cation (Cr3+). However, the relatively low availability of Cr in the urban road environment could influence this behaviour. Comparing total adsorbed metals present in solids particles, it was found that Zn has the highest capacity for adsorption to solids. Desorption experiments confirmed that a low concentration of Cu, Cr and Pb in solids was present in water-soluble and exchangeable form, whilst a significant fraction of adsorbed Zn has a high likelihood of being released back into solution. Among heavy metals, Zn is considered to be the most commonly available metal among road surface pollutants.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

Evaluation of the GHR car following model for traffic safety studies

Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

Microscopic traffic hysteresis in traffic oscillations : a behavioral perspective

This paper studies traffic hysteresis arising in traffic oscillations from a behavioral perspective. It is found that the occurrence and type of traffic hysteresis is closely correlated with driver behavior when experiencing traffic oscillations and with the time driver reaction begins relative to the starting deceleration wave. Statistical results suggest that driver behavior is different depending on its position along the oscillation. This suggests that different car-following models should be used inside the different stages of an oscillation in order to replicate realistic congestion features.