Characterisation and sources of ultrafine particles in an inner city urban area

Exposure to atmospheric ultrafine particles (UFPs, D<100 nm) has been an increasingly concern because of their potential impact one health. Motor vehicle emissions are considered as one of the major source of UFPin urban airshed, as the combustion of both petrol and diesel engine leads to emission of particles which are predominantly in this size range (Ban-Weiss et al, 2010; Morawska et al, 2008). New particle formations (NPFs) and major facilities such as airport or seaport has also been identified as major sources of UFPs in urban airshed (Cheung et al, 2010; González et al, 2011; Mazaheri et al, 2013). However, contribution of those urban sources to ambient UFP concentrations has not been comprehensively characterized.

Effect of atmospheric aging on volatility and reactive oxygen species of biodiesel exhaust nano-particles

In the prospect of limited energy resources and climate change, effects of alternative biofuels on primary emissions are being extensively studied. Our two recent studies have shown that biodiesel fuel composition has a significant impact on primary particulate matter emissions. It was also shown that particulate matter caused by biodiesels was substantially different from the emissions due to petroleum diesel. Emissions appeared to have higher oxidative potential with the increase in oxygen content and decrease of carbon chain length and unsaturation levels of fuel molecules. Overall, both studies concluded that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions. This suggests that the atmospheric aging processes, including secondary organic aerosol formation, of emissions from different fuels will be different as well. In this study, measurements were conducted on a modern common-rail diesel engine. To get more information on realistic properties of tested biodiesel particulate matter once they are released into the atmosphere, particulate matter was exposed to atmospheric oxidants, ozone and ultra-violet light; and the change in their properties was monitored for different biodiesel blends. Upon the exposure to oxidative agents, the chemical composition of the exhaust changes. It triggers the cascade of photochemical reactions resulting in the partitioning of semi-volatile compounds between the gas and particulate phase. In most of the cases, aging lead to the increase in volatility and oxidative potential, and the increment of change was mainly dependent on the chemical composition of fuels as the leading cause for the amount and the type of semi-volatile compounds present in the exhaust.

Concentration levels of heavy metals and polycyclic aromatic hydrocarbons in car parks at Queensland University of Technology

This study investigates the level of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals) in three car parks at QUT, one at Kelvin Grove campus and two at the Gardens Point campus. In addition, comparisons between site designs were assessed to identify the possible sources of heavy metals and PAHs. The main contributing source for heavy metals was identified to be from vehicle debris and emissions, while the source of PAHs was identified to be from petrol and diesel engine vehicle emissions. The highest concentration of pollutants was typically found for the 63 micro meter dust samples, proposed to be due to increased surface areas and thus available adsorption sites.

Particle and gaseous emissions from compressed natural gas and ultralow sulphur diesel-fuelled buses at four steady engine loads

Exhaust emissions from thirteen compressed natural gas (CNG) and nine ultralow sulphur diesel in-service transport buses were monitored on a chassis dynamometer. Measurements were carried out at idle and at three steady engine loads of 25%, 50% and 100% of maximum power at a fixed speed of 60 kmph. Emission factors were estimated for particle mass and number, carbon dioxide and oxides of nitrogen for two types of CNG buses (Scania and MAN, compatible with Euro 2 and 3 emission standards, respectively) and two types of diesel buses (Volvo Pre-Euro/Euro1 and Mercedez OC500 Euro3). All emission factors increased with load. The median particle mass emission factor for the CNG buses was less than 1% of that from the diesel buses at all loads. However, the particle number emission factors did not show a statistically significant difference between buses operating on the two types of fuel. In this paper, for the very first time, particle number emission factors are presented at four steady state engine loads for CNG buses. Median values ranged from the order of 1012 particles min-1 at idle to 1015 particles km-1 at full power. Most of the particles observed in the CNG emissions were in the nanoparticle size range and likely to be composed of volatile organic compounds The CO2 emission factors were about 20% to 30% greater for the diesel buses over the CNG buses, while the oxides of nitrogen emission factors did not show any difference due to the large variation between buses.

Calculation of engine parameters using reconfigurable hardware

The feasibility of real-time calculation of parameters for an internal combustion engine via reconfigurable hardware implementation is investigated as an alternative to software computation. A detailed in-hardware field programmable gate array (FPGA)-based design is developed and evaluated using input crank angle and in-cylinder pressure data from fully instrumented diesel engines in the QUT Biofuel Engine Research Facility (BERF). Results indicate the feasibility of employing a hardware-based implementation for real-time processing for speeds comparable to the data sampling rate currently used in the facility, with acceptably low level of discrepancies between hardware and software-based calculation of key engine parameters.

Performance evaluation of non-thermal plasma on particulate matter, ozone and CO2 correlation for diesel exhaust emission reduction

This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.

Evaluation of functional performance in commercial buildings

This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Betting on the underdog : bricolage as an engine of resource advantage

Resource-based theory posits that firms achieve high performance by controlling resources that are rare, valuable and costly for others to duplicate or work around. Yet scholars have been less successful understanding processes and behaviours by which firms develop such resources. We draw on the behavioral theory of bricolage from the entrepreneurship literature to suggest one such mechanism by which firms may develop such resource-based advantages. The core of our argument is that idiosyncratic bundling processes synonymous with bricolage behavior may create advantageous resource positions by (i) allowing resource constrained firms to allocate more of their limited resources to activities that they view as more strategically important, and (ii) increasing the difficulties other firms face in trying to imitate these advantages. Based on this reasoning we develop several hypotheses which we test in the context of several samples from a large, longitudinal, Australian study of new firm development. The results support our arguments that bricolage will improve a firms’ overall resource positions while generating more areas of strong resource advantage and fewer areas of strong resource disadvantage. We find little support, however, for our arguments that bricolage will make a firms’ key resource advantages more difficult for other firms to imitate. We find some support for our argument that the role of bricolage in creating resource advantages will be enhanced by the quality of the opportunity with which a firm is engaged.

Review of Engine

Review of Engine by NORPA in Lowdown Spetember 2010

Investigating the performance of automatic new topic identification across multiple datasets 1

Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.

Web searcher interaction with the Dogpile.com metasearch engine

Metasearch engines are an intuitive method for improving the performance of Web search by increasing coverage, returning large numbers of results with a focus on relevance, and presenting alternative views of information needs. However, the use of metasearch engines in an operational environment is not well understood. In this study, we investigate the usage of Dogpile.com, a major Web metasearch engine, with the aim of discovering how Web searchers interact with metasearch engines. We report results examining 2,465,145 interactions from 534,507 users of Dogpile.com on May 6, 2005 and compare these results with findings from other Web searching studies. We collect data on geographical location of searchers, use of system feedback, content selection, sessions, queries, and term usage. Findings show that Dogpile.com searchers are mainly from the USA (84% of searchers), use about 3 terms per query (mean = 2.85), implement system feedback moderately (8.4% of users), and generally (56% of users) spend less than one minute interacting with the Web search engine. Overall, metasearchers seem to have higher degrees of interaction than searchers on non-metasearch engines, but their sessions are for a shorter period of time. These aspects of metasearching may be what define the differences from other forms of Web searching. We discuss the implications of our findings in relation to metasearch for Web searchers, search engines, and content providers.

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.

Gaseous and particle emissions from an ethanol fumigated compression ignition engine

A 4-cylinder Ford 2701C test engine was used in this study to explore the impact of ethanol fumigation on gaseous and particle emission concentrations. The fumigation technique delivered vaporised ethanol into the intake manifold of the engine, using an injector, a pump and pressure regulator, a heat exchanger for vaporising ethanol and a separate fuel tank and lines. Gaseous (Nitric oxide (NO), Carbon monoxide (CO) and hydrocarbons (HC)) and particulate emissions (particle mass (PM2.5) and particle number) testing was conducted at intermediate speed (1700 rpm) using 4 load settings with ethanol substitution percentages ranging from 10-40 % (by energy). With ethanol fumigation, NO and PM2.5 emissions were reduced, whereas CO and HC emissions increased considerably and particle number emissions increased at most test settings. It was found that ethanol fumigation reduced the excess air factor for the engine and this led to increased emissions of CO and HC, but decreased emissions of NO. PM2.5 emissions were reduced with ethanol fumigation, as ethanol has a very low “sooting” tendency. This is due to the higher hydrogen-to-carbon ratio of this fuel, and also because ethanol does not contain aromatics, both of which are known soot precursors. The use of a diesel oxidation catalyst (as an after-treatment device) is recommended to achieve a reduction in the four pollutants that are currently regulated for compression ignition engines. The increase in particle number emissions with ethanol fumigation was due to the formation of volatile (organic) particles; consequently, using a diesel oxidation catalyst will also assist in reducing particle number emissions.

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.