Investigation into the transport, behaviour and deposition of combustion aerosols from transport sources

The deterioration of air quality is a significant issue in large and growing cities. This work investigates particulate emissions from transport, the largest source of air pollution in cities today. Emitters such as busy roads and diesel trains are investigated, with specific reference to the evolution of particles over time and distance. Diesel trains are investigated as an alternative to road traffic in investigating evolutionary processes. Higher emissions and solitary sources mean that the emitted plume can be observed over time in a single location. These results represent the first investigation of the evolution of fine and ultrafine aerosol particles from this type of source. Aerosols near a busy road are investigated, with the result that a dependence of total number concentration on distance from the road is shown to be related to the fragmentation of nanoparticle clusters. Local meteorological conditions are also monitored and humidity is shown to vary with distance from the road in a nonmonotonic way. Particles from a busy road were also examined using a scanning electron microscope, with the intention of understanding the make up of the emitted aerosol plume. It was determined that due to significant surface behaviour post-deposition, this method of analysis could not directly classify airborne pollutants. Some interesting results were obtained however, particularly in terms of composite particles and the analysis of deposited patterns. This thesis introduces new work in terms of the analysis of diesel train particulate emissions, as well as adding further evidence towards the fragmentation process of aerosol evolution in both background concentrations and emitted aerosol plumes.

Impact of global warming on the design and performance of air-conditioned office buildings in Australia

As global warming entails new conditions for the built environment, the thermal behavior of existing air conditioned office buildings, which are typically designed based on current weather data, may also change. Through building computer simulations, this paper evaluates the impact of global warming on the design and performance of air-conditioned office buildings in Australia, including the increased cooling loads imposed by potential global warming and probable indoor temperature increases due to possible undersized air-conditioning system, as well as the possible change in energy use and CO2 emission of Australian office buildings. It is found that the existing office buildings would generally be able to adapt to the increasing warmth of 2030 year Low and High scenarios projections and 2070 year Low scenario projection. However, for the 2070 year High scenario, the study indicates that the existing office buildings, in all capital cities except for Hobart, will suffer from overheating problems. If the energy source is assumed to be the electricity, it is found that in comparison with current weather scenario, the increased energy uses would translate into the increase of CO2 emissions by 0 to 34.6 kg CO2 equivalent/m2, varying with different future weather scenarios and with different locations.

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

Evolution of traffic management measures on road traffic noise

Road traffic noise affects the quality of life in the areas adjoining the road. The effect of traffic noise on people is wide ranging and may include sleep disturbance and negative impact on work efficiency. To address the problem of traffic noise, it is necessary to estimate the noise level. For this, a number of noise estimation models have been developed which can estimate noise at the receptor points, based on simple configuration of buildings. However, for a real world situation we have multiple buildings forming built-up area. In such a situation, it is almost impossible to consider multiple diffractions and reflections in sound propagation from the source to the receptor point. An engineering solution to such a real world problem is needed to estimate noise levels in built-up area.

Eco-crime and air pollution

This chapter applies emerging discourses of eco-crime and green criminology to issues of air pollution. Of course there are various forms of pollution, but this chapter will focus on the contamination and regulation of 'the air we breathe'.

Crime is in the air : air pollution and regulation in the UK

This latest briefing by Professor Reece Walters in the What is crime? series, draws attention to an area of harm that is often absent from criminological debate. He highlights the human costs of air pollution and failed attempts to adequately regulate and control such harm. Arguing for a cross disciplinary ‘eco-crime’ narrative, the author calls for greater understanding of the far-reaching consequences of air pollution which could set in train changes which may lead to a ‘more robust and meaningful system of justice’. Describing current arrangements in place to control and regulate air pollution, Walters draws attention to the lack of neutrality in current arrangements and the bias ‘towards the economic imperatives of free trade over and above the centrality of environmental protection’. While attention is often given to direct and individualised instances of ‘crime’, the serious consequences of air pollution are frequently neglected. The negative effects of pollution on health and well-being are often borne by people already experiencing a range of other disadvantages. In a global and national context, it is often the poor who are affected most. Ultimately, political and economic imperatives have historically helped to shape legal and regulatory regimes. Whether this is an inherent flaw in current systems or something that can be overcome in favour of dealing with more wide-ranging harms is an area that requires further discussion and debate.

Prediction of the wash-off of traffic related semi- and non-volatile organic compounds from urban roads under climate change influenced rainfall characteristics

Traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) pose a serious threat to human and ecosystem health when washed off into receiving water bodies by stormwater. Climate change influenced rainfall characteristics makes the estimation of these pollutants in stormwater quite complex. The research study discussed in the paper developed a prediction framework for such pollutants under the dynamic influence of climate change on rainfall characteristics. It was established through principal component analysis (PCA) that the intensity and durations of low to moderate rain events induced by climate change mainly affect the wash-off of SVOCs and NVOCs from urban roads. The study outcomes were able to overcome the limitations of stringent laboratory preparation of calibration matrices by extracting uncorrelated underlying factors in the data matrices through systematic application of PCA and factor analysis (FA). Based on the initial findings from PCA and FA, the framework incorporated orthogonal rotatable central composite experimental design to set up calibration matrices and partial least square regression to identify significant variables in predicting the target SVOCs and NVOCs in four particulate fractions ranging from >300-1 μm and one dissolved fraction of <1 μm. For the particulate fractions range >300-1 μm, similar distributions of predicted and observed concentrations of the target compounds from minimum to 75th percentile were achieved. The inter-event coefficient of variations for particulate fractions of >300-1 μm were 5% to 25%. The limited solubility of the target compounds in stormwater restricted the predictive capacity of the proposed method for the dissolved fraction of <1 μm.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

A behavioural car-following model that captures traffic oscillations

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

Is –110°C cold air cryotherapy effective in improving post-exercise recovery in sports people?

Whole body cryotherapy (WBC) involves repeatedly exposing an individual, dressed in minimal clothing, to extremely cold air (–100 to –130°C) for a short period. One specific claim that is often made is that WBC is effective in treating exercise-induced muscle soreness and damage. However, our results suggest that two bouts of WBC were ineffective in improving recovery from eccentric exercise when administered 24 hours after eccentric exercise.

The effectiveness of traffic policing in reducing traffic crashes

Many governments throughout the world rely heavily on traffic law enforcement programs to modify driver behaviour and enhance road safety. There are two related functions of traffic law enforcement, apprehension and deterrence, and these are achieved through three processes: the establishment of traffic laws, the policing of those laws, and the application of penalties and sanctions to offenders. Traffic policing programs can vary by visibility (overt or covert) and deployment methods (scheduled and non-scheduled), while sanctions can serve to constrain, deter or reform offending behaviour. This chapter will review the effectiveness of traffic law enforcement strategies from the perspective of a range of high-risk, illegal driving behaviours including drink/drug driving, speeding, seat belt use and red light running. Additionally, this chapter discusses how traffic police are increasingly using technology to enforce traffic laws and thus reduce crashes. The chapter concludes that effective traffic policing involves a range of both overt and covert operations and includes a mix of automatic and more traditional manual enforcement methods. It is important to increase both the perceived and actual risk of detection by ensuring that traffic law enforcement operations are sufficiently intensive, unpredictable in nature and conducted as widely as possible across the road network. A key means of maintaining the unpredictability of operations is through the random deployment of enforcement and/or the random checking of drivers. The impact of traffic enforcement is also heightened when it is supported by public education campaigns. In the future, technological improvements will allow the use of more innovative enforcement strategies. Finally, further research is needed to continue the development of traffic policing approaches and address emerging road safety issues.

Navigational traffic conflict technique: a proactive approach to quantitative measurement of collision risks in port waters

Navigational safety analysis relying on collision statistics is often hampered because of low number of observations. A promising alternative approach that overcomes this problem is proposed in this paper. By analyzing critical vessel interactions this approach proactively measures collision risk in port waters. The proposed method is illustrated for quantitative measurement of collision risks in Singapore port fairways, and validated by examining correlations between the measured risks with those perceived by pilots. This method is an ethically appealing alternative to the collision-based analysis for fast, reliable and effective safety assessment, thus possesses great potential for managing collision risks in port waters.