Ions in motor vehicle exhaust and their dispersion near busy roads

Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm-3) was about one-half of that near motorways (1211 cm-3) and about twice as high as that in the urban background (269 cm-3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R2=0.3 at p<0.05) and correlated well with each other in real time (R2=0.87 at p<0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120-150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2m to 5m of the kerb. Measured concentrations decreased to background at about 15m from the kerb when the wind speed was 1.3 m s-1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China

The multi-criteria decision making methods, Preference METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.

The application of a profluorescent nitroxide probe to detect reactive oxygen species derived from combustion-generated particulate matter

Particulate pollution has been widely recognised as an important risk factor to human health. In addition to increases in respiratory and cardiovascular morbidity associated with exposure to particulate matter (PM), WHO estimates that urban PM causes 0.8 million premature deaths globally and that 1.5 million people die prematurely from exposure to indoor smoke generated from the combustion of solid fuels. Despite the availability of a huge body of research, the underlying toxicological mechanisms by which particles induce adverse health effects are not yet entirely understood. Oxidative stress caused by generation of free radicals and related reactive oxygen species (ROS) at the sites of deposition has been proposed as a mechanism for many of the adverse health outcomes associated with exposure to PM. In addition to particle-induced generation of ROS in lung tissue cells, several recent studies have shown that particles may also contain ROS. As such, they present a direct cause of oxidative stress and related adverse health effects. Cellular responses to oxidative stress have been widely investigated using various cell exposure assays. However, for a rapid screening of the oxidative potential of PM, less time-consuming and less expensive, cell-free assays are needed. The main aim of this research project was to investigate the application of a novel profluorescent nitroxide probe, synthesised at QUT, as a rapid screening assay in assessing the oxidative potential of PM. Considering that this was the first time that a profluorescent nitroxide probe was applied in investigating the oxidative stress potential of PM, the proof of concept regarding the detection of PM–derived ROS by using such probes needed to be demonstrated and a sampling methodology needed to be developed. Sampling through an impinger containing profluorescent nitroxide solution was chosen as a means of particle collection as it allowed particles to react with the profluorescent nitroxide probe during sampling, avoiding in that way any possible chemical changes resulting from delays between the sampling and the analysis of the PM. Among several profluorescent nitroxide probes available at QUT, bis(phenylethynyl)anthracene-nitroxide (BPEAnit) was found to be the most suitable probe, mainly due to relatively long excitation and emission wavelengths (λex= 430 nm; λem= 485 and 513 nm). These wavelengths are long enough to avoid overlap with the background fluorescence coming from light absorbing compounds which may be present in PM (e.g. polycyclic aromatic hydrocarbons and their derivatives). Given that combustion, in general, is one of the major sources of ambient PM, this project aimed at getting an insight into the oxidative stress potential of combustion-generated PM, namely cigarette smoke, diesel exhaust and wood smoke PM. During the course of this research project, it was demonstrated that the BPEAnit probe based assay is sufficiently sensitive and robust enough to be applied as a rapid screening test for PM-derived ROS detection. Considering that for all three aerosol sources (i.e. cigarette smoke, diesel exhaust and wood smoke) the same assay was applied, the results presented in this thesis allow direct comparison of the oxidative potential measured for all three sources of PM. In summary, it was found that there was a substantial difference between the amounts of ROS per unit of PM mass (ROS concentration) for particles emitted by different combustion sources. For example, particles from cigarette smoke were found to have up to 80 times less ROS per unit of mass than particles produced during logwood combustion. For both diesel and wood combustion it has been demonstrated that the type of fuel significantly affects the oxidative potential of the particles emitted. Similarly, the operating conditions of the combustion source were also found to affect the oxidative potential of particulate emissions. Moreover, this project has demonstrated a strong link between semivolatile (i.e. organic) species and ROS and therefore, clearly highlights the importance of semivolatile species in particle-induced toxicity.

Environmental aspects and challenges of oilseed produced biodiesel in Southeast Asia

Research on alternative fuel for the vehemently growing number of automotivesis intensified due to environmental reasons rather than turmoil in energy price and supply. From the policy and steps to emphasis the use of biofuel by governments all around the world, this can be comprehended that biofuel have placed itself as a number one substitute for fossil fuels. These phenomena made Southeast Asia a prominent exporter of biodiesel. But thrust in biodiesel production from oilseeds of palm and Jatropha curcas in Malaysia, Indonesia and Thailand is seriously threatening environmental harmony. This paper focuses on this critical issue of biodiesels environmental impacts, policy, standardization of this region as well as on the emission of biodiesel in automotive uses. To draw a bottom line on feasibilities of different feedstock of biodiesel, a critical analysis on oilseed yield rate, land use, engine emissions and oxidation stability is reviewed. Palm oil based biodiesel is clearly ahead in all these aspects of feasibility, except in the case of NOx where it lags from conventional petro diesel.

Influence of hydrocarbon contamination on clay soil microstructure

Microstructural (fabric, forces and composition) changes due to hydrocarbon contamination in a clay soil were studied using Scanning Electron Microscope (micro-fabric analysis), Atomic Force Microscope (forces measurement) and sedimentation bench test (particle size measurements). The non-polluted and polluted glacial till from north-eastern Poland (area of a fuel terminal) were used for the study. Electrostatic repelling forces for the polluted sample were much lower than for the non-polluted sample. In comparison to non-polluted sample, the polluted sample exhibited lower electric charge, attractive forces on approach and strong adhesion on retrieve. The results of the sedimentation tests indicate that clay particles form larger aggregates and settle out of the suspension rapidly in diesel oil. In non-polluted soil, the fabric is strongly aggregated – densely packed, dominate the face-to-face and edge-to-edge types of contacts, clay film tightly adheres to the surface of larger grains and interparticle pores are more common. In polluted soil, the clay matrix is less aggregated – loosely packed, dominate the edge-to-face types of contacts and inter-micro-aggregate pores are more frequent. Substantial differences were observed in the morphometric and geometrical parameters of pore space. The polluted soil micro-fabric proved to be more isotropic and less oriented than in non-polluted soil. The polluted soil, in which electrostatic forces were suppressed by hydrocarbon interaction, displays more open porosity and larger voids than non-polluted soil, which is characterized by occurrence of the strong electrostatic interaction between clay particles.

Development of a diagnostic tool for condition monitoring of rotating machinery

This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

Quantification of particle emission characteristics and development of an emission model for use in transport microenvironments affected by traffic emissions

Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

A physico-chemical characterisation of particulate emissions from a compression ignition engine : the influence of biodiesel feedstock

This study undertook a physico-chemical characterisation of particle emissions from a single compression ignition engine operated at one test mode with 3 biodiesel fuels made from 3 different feedstocks (i.e. soy, tallow and canola) at 4 different blend percentages (20%, 40%, 60% and 80%) to gain insights into their particle-related health effects. Particle physical properties were inferred by measuring particle number size distributions both with and without heating within a thermodenuder (TD) and also by measuring particulate matter (PM) emission factors with an aerodynamic diameter less than 10 μm (PM10). The chemical properties of particulates were investigated by measuring particle and vapour phase Polycyclic Aromatic Hydrocarbons (PAHs) and also Reactive Oxygen Species (ROS) concentrations. The particle number size distributions showed strong dependency on feedstock and blend percentage with some fuel types showing increased particle number emissions, whilst others showed particle number reductions. In addition, the median particle diameter decreased as the blend percentage was increased. Particle and vapour phase PAHs were generally reduced with biodiesel, with the results being relatively independent of the blend percentage. The ROS concentrations increased monotonically with biodiesel blend percentage, but did not exhibit strong feedstock variability. Furthermore, the ROS concentrations correlated quite well with the organic volume percentage of particles – a quantity which increased with increasing blend percentage. At higher blend percentages, the particle surface area was significantly reduced, but the particles were internally mixed with a greater organic volume percentage (containing ROS) which has implications for using surface area as a regulatory metric for diesel particulate matter (DPM) emissions.

An investigation of commuter exposure to ultrafine particles in Sydney

Commuting in various transport modes represents an activity likely to incur significant exposure to traffic emissions. This study investigated the determinants and characteristics of exposure to ultrafine (< 100 nm) particles (UFPs) in four transport modes in Sydney, with a specific focus on exposure in automobiles, which remain the transport mode of choice for approximately 70% of Sydney commuters. UFP concentrations were measured using a portable condensation particle counter (CPC) inside five automobiles commuting on above ground and tunnel roadways, and in buses, ferries and trains. Determinant factors investigated included wind speed, cabin ventilation (automobiles only) and traffic volume. The results showed that concentrations varied significantly as a consequence of transport mode, vehicle type and ventilation characteristics. The effects of wind speed were minimal relative to those of traffic volume (especially heavy diesel vehicles) and cabin ventilation, with the latter proving to be a strong determinant of UFP ingress into automobiles. The effect of ~70 minutes of commuting on total daily exposure was estimated using a range of UFP concentrations reported for several microenvironments. A hypothetical Sydney resident commuting by automobile and spending 8.5 minutes of their day in the M5 East tunnel could incur anywhere from a lower limit of 3-11% to an upper limit of 37-69% of daily UFP exposure during a return commute, depending on the concentrations they encountered in other microenvironments, the type of vehicle they used and the ventilation setting selected. However, commute-time exposures at either extreme of the values presented are unlikely to occur in practice. The range of exposures estimated for other transport modes were comparable to those of automobiles, and in the case of buses, higher than automobiles.

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.

Characterisation and source identification of selected pollutants in house dust

House dust is a heterogeneous matrix, which contains a number of biological materials and particulate matter gathered from several sources. It is the accumulation of a number of semi-volatile and non-volatile contaminants. The contaminants are trapped and preserved. Therefore, house dust can be viewed as an archive of both the indoor and outdoor air pollution. There is evidence to show that on average, people tend to stay indoors most of the time and this increases exposure to house dust. The aims of this investigation were to: " assess the levels of Polycyclic Aromatic Hydrocarbons (PAHs), elements and pesticides in the indoor environment of the Brisbane area; " identify and characterise the possible sources of elemental constituents (inorganic elements), PAHs and pesticides by means of Positive Matrix Factorisation (PMF); and " establish the correlations between the levels of indoor air pollutants (PAHs, elements and pesticides) with the external and internal characteristics or attributes of the buildings and indoor activities by means of multivariate data analysis techniques. The dust samples were collected during the period of 2005-2007 from homes located in different suburbs of Brisbane, Ipswich and Toowoomba, in South East Queensland, Australia. A vacuum cleaner fitted with a paper bag was used as a sampler for collecting the house dust. A survey questionnaire was filled by the house residents which contained information about the indoor and outdoor characteristics of their residences. House dust samples were analysed for three different pollutants: Pesticides, Elements and PAHs. The analyses were carried-out for samples of particle size less than 250 µm. The chemical analyses for both pesticides and PAHs were performed using a Gas Chromatography Mass Spectrometry (GC-MS), while elemental analysis was carried-out by using Inductively-Coupled Plasma-Mass Spectroscopy (ICP-MS). The data was subjected to multivariate data analysis techniques such as multi-criteria decision-making procedures, Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE), coupled with Geometrical Analysis for Interactive Aid (GAIA) in order to rank the samples and to examine data display. This study showed that compared to the results from previous works, which were carried-out in Australia and overseas, the concentrations of pollutants in house dusts in Brisbane and the surrounding areas were relatively very high. The results of this work also showed significant correlations between some of the physical parameters (types of building material, floor level, distance from industrial areas and major road, and smoking) and the concentrations of pollutants. Types of building materials and the age of houses were found to be two of the primary factors that affect the concentrations of pesticides and elements in house dust. The concentrations of these two types of pollutant appear to be higher in old houses (timber houses) than in the brick ones. In contrast, the concentrations of PAHs were noticed to be higher in brick houses than in the timber ones. Other factors such as floor level, and distance from the main street and industrial area, also affected the concentrations of pollutants in the house dust samples. To apportion the sources and to understand mechanisms of pollutants, Positive Matrix Factorisation (PMF) receptor model was applied. The results showed that there were significant correlations between the degree of concentration of contaminants in house dust and the physical characteristics of houses, such as the age and the type of the house, the distance from the main road and industrial areas, and smoking. Sources of pollutants were identified. For PAHs, the sources were cooking activities, vehicle emissions, smoking, oil fumes, natural gas combustion and traces of diesel exhaust emissions; for pesticides the sources were application of pesticides for controlling termites in buildings and fences, treating indoor furniture and in gardens for controlling pests attacking horticultural and ornamental plants; for elements the sources were soil, cooking, smoking, paints, pesticides, combustion of motor fuels, residual fuel oil, motor vehicle emissions, wearing down of brake linings and industrial activities.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Physicochemical characterization of particulate emissions from a compression ignition engine employing two injection technologies and three fuels

Alternative fuels and injection technologies are a necessary component of particulate emission reduction strategies for compression ignition engines. Consequently, this study undertakes a physicochemical characterization of diesel particulate matter (DPM) for engines equipped with alternative injection technologies (direct injection and common rail) and alternative fuels (ultra low sulfur diesel, a 20% biodiesel blend, and a synthetic diesel). Particle physical properties were addressed by measuring particle number size distributions, and particle chemical properties were addressed by measuring polycyclic aromatic hydrocarbons (PAHs) and reactive oxygen species (ROS). Particle volatility was determined by passing the polydisperse size distribution through a thermodenuder set to 300 °C. The results from this study, conducted over a four point test cycle, showed that both fuel type and injection technology have an impact on particle emissions, but injection technology was the more important factor. Significant particle number emission (54%–84%) reductions were achieved at half load operation (1% increase–43% decrease at full load) with the common rail injection system; however, the particles had a significantly higher PAH fraction (by a factor of 2 to 4) and ROS concentrations (by a factor of 6 to 16) both expressed on a test-cycle averaged basis. The results of this study have significant implications for the health effects of DPM emissions from both direct injection and common rail engines utilizing various alternative fuels.

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.