Particle number and mass emission factors from combustion of wood samples collected from Queensland forest

Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

At-the-edge-of-the-forest

This exhibition was the outcome of a personal arts-based exploration of the meaning of interiority. Through the process it was found that existentially the architectural wall differentiating inside from outside does not exist but operates as a space of overlap, a groundless ground providing for dwelling in the real existential sense of the word.

Comparative study : health research on traffic noise pollution vs. Technical research on traffic noise mitigation

Community awareness and the perception on the traffic noise related health impacts have increased significantly over the last decade resulting in a large volume of public inquiries flowing to Road Authorities for planning advice. Traffic noise management in the urban environment is therefore becoming a “social obligation”, essentially due to noise related health concerns. Although various aspects of urban noise pollution and mitigation have been researched independently, an integrated approach by stakeholders has not been attempted. Although the current treatment and mitigation strategies are predominantly handled by the Road Agencies, a concerted effort by all stakeholders is becoming mandatory for effective and tangible outcomes in the future. A research project is underway a RMIT University, Australia, led by the second author to consider the use of “hedonic pricing” for alternative noise amelioration treatments within the road reserve and outside the road reserve. The project aims to foster a full range noise abatement strategy encompassing source, path and noise receiver. The benefit of such a study would be to mitigate the problem where it is most effective and would defuse traditional “authority” boundaries to produce the optimum outcome. The project is conducted in collaboration with the Department of Main Roads Queensland, Australia and funded by the CRC for Construction Innovation. As part of this study, a comprehensive literature search is currently underway to investigate the advancements in community health research, related to environmental noise pollution, and the advancements in technical and engineering research in mitigating the issue. This paper presents the outcomes of this work outlining state of the art, national and international good practices and gap analysis to identify major anomalies and developments.

Race and equity in higher education : A harder path for Indigenous academics

Our experiences as Indigenous academics within universities often reflects the experiences we have as Indigenous people in broader society, yet I am still surprised and angered when it is others working in higher education who espouse notions of justice and equity with whom we experience tension and conflict in asserting our rights, values and cultural values. At times it is a constant struggle even when universities have Reconciliation Statements as most of them do now, Indigenous recruitment or employment strategies and university wide anti-racism and anti-discrimination policies and procedures.

Computational approach to localization using global energy minimization

Damage localization induced by strain softening can be predicted by the direct minimization of a global energy function. This article concerns the computational strategy for implementing this principle for softening materials such as concrete. Instead of using heuristic global optimization techniques, our strategies are a hybrid of local optimization methods with a path-finding approach to ensure a global optimum. With admissible nodal displacements being independent variables, it is easy to deal with the geometric (mesh) constraint conditions. The direct search optimization methods recover the localized solutions for a range of softening lattice models which are representative of quasi-brittle structures

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

Young children learning for the environment: Researching a forest adventure

Field experiences for young children are an ideal medium for environmental education/education for sustainability because of opportunities for direct experience in nature, integrated learning, and high community involvement. This research documented the development - in 4-5 year old Prep children - of knowledge, attitudes and actions/advocacy in support of an endangered native Australian animal, the Greater Bilby. Data indicated that children gained new knowledge, changed attitudes and built a repertoire of action/ advocacy strategies in native animal conservation as a result of participating in a forest field adventure. The curriculum and pedagogical features that supported these young children’s learning include: active engagement in a natural environment, learning through curriculum integration at home and at school, anthropomorphic representations of natural elements, making connections with cultural practices, and intergenerational learning. The paper also highlights research strategies that can be usefully and ethically applied when conducting studies involving young children.

Determinants of participation restriction among community dwelling stroke survivors : a path analysis

Background: Apart from promoting physical recovery and assisting in activities of daily living, a major challenge in stroke rehabilitation is to minimize psychosocial morbidity and to promote the reintegration of stroke survivors into their family and community. The identification of key factors influencing long-term outcome are essential in developing more effective rehabilitation measures for reducing stroke-related morbidity. The aim of this study was to test a theoretical model of predictors of participation restriction which included the direct and indirect effects between psychosocial outcomes, physical outcome, and socio-demographic variables at 12 months after stroke.--------- Methods: Data were collected from 188 stroke survivors at 12 months following their discharge from one of the two rehabilitation hospitals in Hong Kong. The settings included patients' homes and residential care facilities. Path analysis was used to test a hypothesized model of participation restriction at 12 months.---------- Results: The path coefficients show functional ability having the largest direct effect on participation restriction (β = 0.51). The results also show that more depressive symptoms (β = -0.27), low state self-esteem (β = 0.20), female gender (β = 0.13), older age (β = -0.11) and living in a residential care facility (β = -0.12) have a direct effect on participation restriction. The explanatory variables accounted for 71% of the variance in explaining participation restriction at 12 months.---------- Conclusion: Identification of stroke survivors at risk of high levels of participation restriction, depressive symptoms and low self-esteem will assist health professionals to devise appropriate rehabilitation interventions that target improving both physical and psychosocial functioning.