Role of traffic in atmospheric accumulation of heavy metals and polycyclic aromatic hydrocarbons

Traffic related emissions have been recognised as one of the main sources of air pollutants. In the research study discussed in this paper, variability of atmospheric total suspended particulate matter (TSP), polycyclic aromatic hydrocarbons (PAH) and heavy metal (HM) concentrations with traffic and land use characteristics during weekdays and weekends were investigated. Data required for the study were collected from a range of sampling sites to ensure a wide mix of traffic and land use characteristics. The analysis undertaken confirmed that zinc has the highest concentration in the atmospheric phase during weekends as well as weekdays. Although the use of leaded gasoline was discontinued a decade ago, lead was the second most commonly detected heavy metal. This is attributed to the association of previously generated lead with roadside soil and re-suspension to the atmosphere. Soil related particles are the primary source of TSP and manganese to the atmosphere. The analysis further revealed that traffic sources are dominant in gas phase PAHs compared to the other sources during weekdays. Land use related sources become important contributors to atmospheric PAHs during weekends when traffic sources are at their minimal levels.

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.

Calibration, estimation, and sampling issues of car-following parameters

Drivers behave in different ways, and these different behaviors are a cause of traffic disturbances. A key objective for simulation tools is to correctly reproduce this variability, in particular for car-following models. From data collection to the sampling of realistic behaviors, a chain of key issues must be addressed. This paper discusses data filtering, robustness of calibration, correlation between parameters, and sampling techniques of acceleration-time continuous car-following models. The robustness of calibration is systematically investigated with an objective function that allows confidence regions around the minimum to be obtained. Then, the correlation between sets of calibrated parameters and the validity of the joint distributions sampling techniques are discussed. This paper confirms the need for adapted calibration and sampling techniques to obtain realistic sets of car-following parameters, which can be used later for simulation purposes.

Study of baleen whales’ ecology and interaction with maritime traffic activities to support management of a complex socio-ecological system

Thesis written in co-mentorship with Robert Michaud.

Insights into the dynamics and sources of atmospheric lead and particulate matter in Sao Paulo, Brazil, from high temporal resolution sampling

We present the first results of a study investigating the processes that control concentrations and sources of Pb and particulate matter in the atmosphere of Sao Paulo City Brazil Aerosols were collected with high temporal resolution (3 hours) during a four-day period in July 2005 The highest Pb concentrations measured coincided with large fireworks during celebration events and associated to high traffic occurrence Our high-resolution data highlights the impact that a singular transient event can have on air quality even in a megacity Under meteorological conditions non-conducive to pollutant dispersion Pb and particulate matter concentrations accumulated during the night leading to the highest concentrations in aerosols collected early in the morning of the following day The stable isotopes of Pb suggest that emissions from traffic remain an Important source of Pb in Sao Paulo City due to the large traffic fleet despite low Pb concentrations in fuels (C) 2010 Elsevier BV All rights reserved

Use of passive diffusion sampling method for defining NO2 concentrations gradient in São Paulo, Brazil

Abstract Background Air pollution in São Paulo is constantly being measured by the State of Sao Paulo Environmental Agency, however there is no information on the variation between places with different traffic densities. This study was intended to identify a gradient of exposure to traffic-related air pollution within different areas in São Paulo to provide information for future epidemiological studies. Methods We measured NO2 using Palmes' diffusion tubes in 36 sites on streets chosen to be representative of different road types and traffic densities in São Paulo in two one-week periods (July and August 2000). In each study period, two tubes were installed in each site, and two additional tubes were installed in 10 control sites. Results Average NO2 concentrations were related to traffic density, observed on the spot, to number of vehicles counted, and to traffic density strata defined by the city Traffic Engineering Company (CET). Average NO2concentrations were 63μg/m3 and 49μg/m3 in the first and second periods, respectively. Dividing the sites by the observed traffic density, we found: heavy traffic (n = 17): 64μg/m3 (95% CI: 59μg/m3 – 68μg/m3); local traffic (n = 16): 48μg/m3 (95% CI: 44μg/m3 – 52μg/m3) (p < 0.001). Conclusion The differences in NO2 levels between heavy and local traffic sites are large enough to suggest the use of a more refined classification of exposure in epidemiological studies in the city. Number of vehicles counted, traffic density observed on the spot and traffic density strata defined by the CET might be used as a proxy for traffic exposure in São Paulo when more accurate measurements are not available.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Guide to urban traffic volume counting. Final report.

Federal Highway Administration, Urban Planning Division, Washington, D.C.

National Accident Sampling System. Report of a meeting.

Mode of access: Internet.

The effect of using a 'towaway' threshold in studying traffic accidents. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Accident causation methodology development for the National Accident Sampling System: final report.

National Highway Traffic Safety Administration, Washington, D.C.

National Accident Sampling System sample design - phases 2 and 3 - executive summary. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

National Accident Sampling System sample design - phases 2 and 3. Volume II: exhibits. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

National accident sampling system crashworthiness data system 1988-1990.

Mode of access: Internet.

National accident sampling system crashworthiness data system 1991-1993.

Mode of access: Internet.