Uncertainty budget in the measurement of typical airborne number, surface area and mass particle distributions

The effects of particulate matter on environment and public health have been widely studied in recent years. A number of studies in the medical field have tried to identify the specific effect on human health of particulate exposure, but agreement amongst these studies on the relative importance of the particles’ size and its origin with respect to health effects is still lacking. Nevertheless, air quality standards are moving, as the epidemiological attention, towards greater focus on the smaller particles. Current air quality standards only regulate the mass of particulate matter less than 10 μm in aerodynamic diameter (PM10) and less than 2.5 μm (PM2.5). The most reliable method used in measuring Total Suspended Particles (TSP), PM10, PM2.5 and PM1 is the gravimetric method since it directly measures PM concentration, guaranteeing an effective traceability to international standards. This technique however, neglects the possibility to correlate short term intra-day variations of atmospheric parameters that can influence ambient particle concentration and size distribution (emission strengths of particle sources, temperature, relative humidity, wind direction and speed and mixing height) as well as human activity patterns that may also vary over time periods considerably shorter than 24 hours. A continuous method to measure the number size distribution and total number concentration in the range 0.014 – 20 μm is the tandem system constituted by a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). In this paper, an uncertainty budget model of the measurement of airborne particle number, surface area and mass size distributions is proposed and applied for several typical aerosol size distributions. The estimation of such an uncertainty budget presents several difficulties due to i) the complexity of the measurement chain, ii) the fact that SMPS and APS can properly guarantee the traceability to the International System of Measurements only in terms of number concentration. In fact, the surface area and mass concentration must be estimated on the basis of separately determined average density and particle morphology. Keywords: SMPS-APS tandem system, gravimetric reference method, uncertainty budget, ultrafine particles.

Development of a particle number and particle mass emissions inventory for an urban fleet : a study in South-East Queensland

Motor vehicles are a major source of gaseous and particulate matter pollution in urban areas, particularly of ultrafine sized particles (diameters < 0.1 µm). Exposure to particulate matter has been found to be associated with serious health effects, including respiratory and cardiovascular disease, and mortality. Particle emissions generated by motor vehicles span a very broad size range (from around 0.003-10 µm) and are measured as different subsets of particle mass concentrations or particle number count. However, there exist scientific challenges in analysing and interpreting the large data sets on motor vehicle emission factors, and no understanding is available of the application of different particle metrics as a basis for air quality regulation. To date a comprehensive inventory covering the broad size range of particles emitted by motor vehicles, and which includes particle number, does not exist anywhere in the world. This thesis covers research related to four important and interrelated aspects pertaining to particulate matter generated by motor vehicle fleets. These include the derivation of suitable particle emission factors for use in transport modelling and health impact assessments; quantification of motor vehicle particle emission inventories; investigation of the particle characteristic modality within particle size distributions as a potential for developing air quality regulation; and review and synthesis of current knowledge on ultrafine particles as it relates to motor vehicles; and the application of these aspects to the quantification, control and management of motor vehicle particle emissions. In order to quantify emissions in terms of a comprehensive inventory, which covers the full size range of particles emitted by motor vehicle fleets, it was necessary to derive a suitable set of particle emission factors for different vehicle and road type combinations for particle number, particle volume, PM1, PM2.5 and PM1 (mass concentration of particles with aerodynamic diameters < 1 µm, < 2.5 µm and < 10 µm respectively). The very large data set of emission factors analysed in this study were sourced from measurement studies conducted in developed countries, and hence the derived set of emission factors are suitable for preparing inventories in other urban regions of the developed world. These emission factors are particularly useful for regions with a lack of measurement data to derive emission factors, or where experimental data are available but are of insufficient scope. The comprehensive particle emissions inventory presented in this thesis is the first published inventory of tailpipe particle emissions prepared for a motor vehicle fleet, and included the quantification of particle emissions covering the full size range of particles emitted by vehicles, based on measurement data. The inventory quantified particle emissions measured in terms of particle number and different particle mass size fractions. It was developed for the urban South-East Queensland fleet in Australia, and included testing the particle emission implications of future scenarios for different passenger and freight travel demand. The thesis also presents evidence of the usefulness of examining modality within particle size distributions as a basis for developing air quality regulations; and finds evidence to support the relevance of introducing a new PM1 mass ambient air quality standard for the majority of environments worldwide. The study found that a combination of PM1 and PM10 standards are likely to be a more discerning and suitable set of ambient air quality standards for controlling particles emitted from combustion and mechanically-generated sources, such as motor vehicles, than the current mass standards of PM2.5 and PM10. The study also reviewed and synthesized existing knowledge on ultrafine particles, with a specific focus on those originating from motor vehicles. It found that motor vehicles are significant contributors to both air pollution and ultrafine particles in urban areas, and that a standardized measurement procedure is not currently available for ultrafine particles. The review found discrepancies exist between outcomes of instrumentation used to measure ultrafine particles; that few data is available on ultrafine particle chemistry and composition, long term monitoring; characterization of their spatial and temporal distribution in urban areas; and that no inventories for particle number are available for motor vehicle fleets. This knowledge is critical for epidemiological studies and exposure-response assessment. Conclusions from this review included the recommendation that ultrafine particles in populated urban areas be considered a likely target for future air quality regulation based on particle number, due to their potential impacts on the environment. The research in this PhD thesis successfully integrated the elements needed to quantify and manage motor vehicle fleet emissions, and its novelty relates to the combining of expertise from two distinctly separate disciplines - from aerosol science and transport modelling. The new knowledge and concepts developed in this PhD research provide never before available data and methods which can be used to develop comprehensive, size-resolved inventories of motor vehicle particle emissions, and air quality regulations to control particle emissions to protect the health and well-being of current and future generations.

X-ray computed tomography

X-ray computed tomography (CT) is a medical imaging technique that produces images of trans-axial planes through the human body. When compared with a conventional radiograph, which is an image of many planes superimposed on each other, a CT image exhibits significantly improved contrast although this is at the expense of reduced spatial resolution.----- A CT image is reconstructed mathematically from a large number of one dimensional projections of the chosen plane. These projections are acquired electronically using a linear array of solid-state detectors and an x ray source that rotates around the patient.----- X-ray computed tomography is used routinely in radiological examinations. It has also be found to be useful in special applications such as radiotherapy treatment planning and three-dimensional imaging for surgical planning.

Strategies for comparing decimal numbers with the same whole-number part

The strategies employed by 130 Grade 5 Brisbane students in comparing decimal numbers which have the same whole-number part were compared with those identified in similar studies conducted in the USA, France and Israel. Three new strategies were identified. Similar to USA results, the most common comparison errors stemmed from the incorrect whole-number strategy in which length is confused with size. The findings of this present study tend to support Resnick et al.’s (1989) hypothesis that the introduction of decimal-fraction recording before common-fraction recording seems to promote better comparison of decimal numbers.

Construction of multiplicative abstract schema for decimal-number numeration

This paper reports on an intervention study planned to help Year 6 students construct the multiplicative structure underlying decimal-number numeration. Three types of intervention were designed from a numeration model developed from a large study of 173 Year 6 students’ decimal-number knowledge. The study found that students could acquire multiplicative structure as an abstract schema if instruction took account of prior knowledge as informed by the model.

Fractions, reunitisation and the number-line representation

Centre for Mathematics and Science Education, QUT, Brisbane, Australia This paper reports on a study in which Years 6 and 10 students were individually interviewed to determine their ability to unitise and reunitise number lines used to represent mixed numbers and improper fractions. Only 16.7% of the students (all Year 6) were successful on all three tasks and, in general, Year 6 students outperformed Year 8 students. The interviews revealed that the remaining students had incomplete, fragmented or non-existent structural knowledge of mixed numbers and improper fractions, and were unable to unitise or reunitise number lines. The implication for teaching is that instruction should focus on providing students with a variety of fraction representations in order to develop rich and flexible schema for all fraction types (mixed numbers, and proper and improper fractions).

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Generic decoupled image-based visual servoing for cameras obeying the unified projection model

In this paper a generic decoupled imaged-based control scheme for calibrated cameras obeying the unified projection model is proposed. The proposed decoupled scheme is based on the surface of object projections onto the unit sphere. Such features are invariant to rotational motions. This allows the control of translational motion independently from the rotational motion. Finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6 dofs robot platform.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Critical analysis of high particle number emissions from accelerating compressed natural gas buses

Compressed natural gas (CNG) engines are thought to be less harmful to the environment than conventional diesel engines, especially in terms of particle emissions. Although, this is true with respect to particulate matter (PM) emissions, results of particle number (PN) emission comparisons have been inconclusive. In this study, results of on-road and dynamometer studies of buses were used to derive several important conclusions. We show that, although PN emissions from CNG buses are significantly lower than from diesel buses at low engine power, they become comparable at high power. For diesel buses, PN emissions are not significantly different between acceleration and operation at steady maximum power. However, the corresponding PN emissions from CNG buses when accelerating are an order of magnitude greater than when operating at steady maximum power. During acceleration under heavy load, PN emissions from CNG buses are an order of magnitude higher than from diesel buses. The particles emitted from CNG buses are too small to contribute to PM10 emissions or contribute to a reduction of visibility, and may consist of semivolatile nanoparticles.

Decoupled image-based visual servoing for cameras obeying the unified projection model

This paper proposes a generic decoupled imagebased control scheme for cameras obeying the unified projection model. The scheme is based on the spherical projection model. Invariants to rotational motion are computed from this projection and used to control the translational degrees of freedom. Importantly we form invariants which decrease the sensitivity of the interaction matrix to object depth variation. Finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6-DOF robotic platform.