Physical, chemical, biological and ecotoxicological properties of wastewater discharged from Davis Station, Antarctica

The properties and toxicity of untreatedwastewater at Davis Station, East Antarctica,were investigated to inform decisions regarding the appropriate level of treatment for local discharge purposes and more generally, to better understand the risk associated with dispersal and impact of wastewaters in Antarctica. Suspended solids, nutrients (nitrogen, phosphorus), biological oxygen demand (BOD), metals, organic contaminants, surfactants and microbiological load were measured at various locations throughout the wastewater discharge system. Wastewater quality and properties varied greatly between buildings on station, each ofwhich has separate holding tanks. Nutrients, BOD and settleable solid levelswere higher than standard municipal wastewaters. Microbiological loads were typical of untreated wastewater. Contaminants detected in the wastewater included metals and persistent organic compounds, mainly polybrominated diphenyl ethers (PBDEs). The toxicity of wastewater was also investigated in laboratory bioassays using two local Antarctic marine invertebrates, the amphipod Paramoera walkeri and the microgastropod Skenella paludionoides. Animals were exposed to a range of wastewater concentrations from3% to 68% (test 1) or 63% (test 2) over 21 days with survival monitored daily. Significant mortality occurred in all concentrations of wastewater after 14 to 21 days, and at higher concentrations (50–68% wastewater) mortality occurred after only one day. Results indicate that the local receiving marine environment at Davis Station is at risk from existing wastewater discharges, and that advanced treatment is required both to remove contaminants shown to cause toxicity to biota, as well as to reduce the environmental risks associated with non-native micro-organisms in wastewater.

Analysing governance of Australia's system of landscape-based greenhouse gas abatement

Healthy governance systems are key to delivering effective outcomes in any broad domain of natural resource management (NRM). One of Australia's emerging NRM governance domains is our national framework for greenhouse gas abatement (GGA), as delivered through a wide range of management practices in the Australian landscape. The emerging Landscape-Based GGA Domain represents an innovative governance space that straddles both the nation's broader NRM Policy and Delivery Domain and Australia's GGA Domain. As a point-in-time benchmark, we assess the health of this hybrid domain as it stood at the end of 2013. At that time, the domain was being progressed through the Australian government's Clean Energy Package and, more particularly, its Carbon Farming Initiative (CFI). While significant changes are currently under development by a new Australian government, this paper explores key areas of risk within the governance system underpinning this emerging hybrid domain at that point in time. We then map some potential reform or continuous improvement pathways required (from national to paddock scale) with the view to securing improved landscape outcomes over time through widespread GGA activities.

Reactive reaching and grasping on a humanoid: Towards closing the action-perception loop on the iCub

We propose a system incorporating a tight integration between computer vision and robot control modules on a complex, high-DOF humanoid robot. Its functionality is showcased by having our iCub humanoid robot pick-up objects from a table in front of it. An important feature is that the system can avoid obstacles - other objects detected in the visual stream - while reaching for the intended target object. Our integration also allows for non-static environments, i.e. the reaching is adapted on-the-fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. Furthermore we show that this system can be used both in autonomous and tele-operation scenarios.

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.

Turbulence and Mixing in the Environment: Multi-Device Study in a Sub-tropical Estuary

In an estuary, mixing and dispersion result from a combination of large-scale advection and smallscale turbulence, which are complex to estimate. The predictions of scalar transport and mixing are often inferred and rarely accurate, due to inadequate understanding of the contributions of these difference scales to estuarine recirculation. A multi-device field study was conducted in a small sub-tropical estuary under neap tide conditions with near-zero fresh water discharge for about 48 hours. During the study, acoustic Doppler velocimeters (ADV) were sampled at high frequency (50 Hz), while an acoustic Doppler current profiler (ADCP) and global positioning system (GPS) tracked drifters were used to obtain some lower frequency spatial distribution of the flow parameters within the estuary. The velocity measurements were complemented with some continuous measurement of water depth, conductivity, temperature and some other physiochemical parameters. Thorough quality control was carried out by implementation of relevant error removal filters on the individual data set to intercept spurious data. A triple decomposition (TD) technique was introduced to access the contributions of tides, resonance and ‘true’ turbulence in the flow field. The time series of mean flow measurements for both the ADCP and drifter were consistent with those of the mean ADV data when sampled within a similar spatial domain. The tidal scale fluctuation of velocity and water level were used to examine the response of the estuary to tidal inertial current. The channel exhibited a mixed type wave with a typical phase-lag between 0.035π– 0.116π. A striking feature of the ADV velocity data was the slow fluctuations, which exhibited large amplitudes of up to 50% of the tidal amplitude, particularly in slack waters. Such slow fluctuations were simultaneously observed in a number of physiochemical properties of the channel. The ensuing turbulence field showed some degree of anisotropy. For all ADV units, the horizontal turbulence ratio ranged between 0.4 and 0.9, and decreased towards the bed, while the vertical turbulence ratio was on average unity at z = 0.32 m and approximately 0.5 for the upper ADV (z = 0.55 m). The result of the statistical analysis suggested that the ebb phase turbulence field was dominated by eddies that evolved from ejection type process, while that of the flood phase contained mixed eddies with significant amount related to sweep type process. Over 65% of the skewness values fell within the range expected of a finite Gaussian distribution and the bulk of the excess kurtosis values (over 70%) fell within the range of -0.5 and +2. The TD technique described herein allowed the characterisation of a broader temporal scale of fluctuations of the high frequency data sampled within the durations of a few tidal cycles. The study provides characterisation of the ranges of fluctuation required for an accurate modelling of shallow water dispersion and mixing in a sub-tropical estuary.

Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

Dynamics of reverse salience as technological performance gap: An empirical study of the personal computer technology system

The evolution of technological systems is hindered by systemic components, referred to as reverse salients, which fail to deliver the necessary level of technological performance thereby inhibiting the performance delivery of the system as a whole. This paper develops a performance gap measure of reverse salience and applies this measurement in the study of the PC (personal computer) technological system, focusing on the evolutions of firstly the CPU (central processing unit) and PC game sub-systems, and secondly the GPU (graphics processing unit) and PC game sub-systems. The measurement of the temporal behavior of reverse salience indicates that the PC game sub-system is the reverse salient, continuously trailing behind the technological performance of the CPU and GPU sub-systems from 1996 through 2006. The technological performance of the PC game sub-system as a reverse salient trails that of the CPU sub-system by up to 2300 MHz with a gradually decreasing performance disparity in recent years. In contrast, the dynamics of the PC game sub-system as a reverse salient trails the GPU sub-system with an ever increasing performance gap throughout the timeframe of analysis. In addition, we further discuss the research and managerial implications of our findings.

Robotic detection and tracking of Crown-Of-Thorns starfish

This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.

LED lighting design strategies to enhance window appearance and increase energy savings in daylit office spaces

Vertical windows are the most common and simplest method to introduce daylight to interior spaces of office buildings, while also providing a view and connection to the outside. However, high contrast ratios between windows and surrounding surfaces can cause visual discomfort for occupants and can negatively influence their health and productivity. Consequently, building occupants may try to adapt their working environment through closing blinds and turning on lights in order to improve indoor visual comfort. Such interventions defeat the purpose of daylight harvesting systems and can increase the forecast electric lighting consumption in buildings that include such systems. A simple strategy to prevent these problematic consequences is to reduce the luminance contrasts presented by the window wall by increasing the luminance of areas surrounding the window through the sparing use of energy-efficient supplementary lighting, such light emitting diodes (LEDs). This paper presents the result of a pilot study in typical office in Brisbane, Australia that tests the effectiveness of a supplementary LED lighting system. The study shows an improvement in the appraisal of the visual environment is achieved using the supplementary system, along with up to 88% reductions in luminance contrast at the window wall. Also observed is a 36% reduction in the likelihood of user interventions that would increase energy usage. These results are used as the basis of an annual energy simulation of the test office and indicate that supplementary systems could be used to save energy beyond what is typically realised in side lit office spaces.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.