Discussion paper and working paper series : Motivations, expectations and experiences of Australian rural and regional planners

Despite playing an extremely important role in shaping communities, the role and contribution of planners is not widely understood or acknowledged. At the same time, there is a shortage of planners in Australia, especially in non-urban areas. Thus, though an online survey of 185 rural and regional planners, this research explores their motivations, expectations and experiences. Most enjoyed and felt confident in their role, explaining that they valued the relaxed family orientated rural lifestyle and the varied nature of the planning work. Although they sometimes felt isolated, the non-urban location provided quicker progression to senior roles, the ability to engage directly with the community and to see the consequences of their decisions. Only half felt their education had prepared them well for their role, citing gaps in terms of computerised modelling, team leadership and conflict resolution skills. Their feedback centred on providing a more practical course, focussing more on regional planning, and encouraging urban and rural experience placements. As the first study to quantifiably explore rural and regional Australian planners perceptions of their role and challenges, the findings illustrate current experiences, key planning challenges, perceived educational gaps and future priorities.

Impact of recent coastal development and human activities on Nha Trang Bay, Vietnam : evidence from a Porites lutea geochemical record

Nha Trang Bay (NTB) is located on the Central Vietnam coast, western South China Sea. Recent coastal development of Nha Trang City has raised public concern over an increasing level of pollution within the bay and degradation of nearby coral reefs. In this study, multiple proxies (e.g., trace metals, rare earth elements (REEs), and Y/Ho) recorded in a massive Porites lutea coral colony were used to reconstruct changes in seawater conditions in the NTB from 1995 to 2009. A 14-year record of REEs and other trace metals revealed that the concentrations of terrestrial trace metals have increased dramatically in response to an increase in coastal development projects such as road, port, and resort constructions, port and river dredging, and dumping activities since 2000. The effects of such developmental processes are also evident in changes in REE patterns and Y/Ho ratios through time, suggesting that both parameters are critical proxies for marine pollution.

Changes to airborne pollen counts across Europe

A progressive global increase in the burden of allergic diseases has affected the industrialized world over the last half century and has been reported in the literature. The clinical evidence reveals a general increase in both incidence and prevalence of respiratory diseases, such as allergic rhinitis (common hay fever) and asthma. Such phenomena may be related not only to air pollution and changes in lifestyle, but also to an actual increase in airborne quantities of allergenic pollen. Experimental enhancements of carbon dioxide (CO) have demonstrated changes in pollen amount and allergenicity, but this has rarely been shown in the wider environment. The present analysis of a continental-scale pollen data set reveals an increasing trend in the yearly amount of airborne pollen for many taxa in Europe, which is more pronounced in urban than semi-rural/rural areas. Climate change may contribute to these changes, however increased temperatures do not appear to be a major influencing factor. Instead, we suggest the anthropogenic rise of atmospheric CO levels may be influential.

Fuel consumption and gas emissions of an automatic transmission vehicle following simple eco-driving instructions on urban roads

Following eco-driving instructions can reduce fuel consumption between 5 to 20% on urban roads with manual cars. The majority of Australian cars have an automatic transmission gear-box. It is therefore of interest to verify whether current eco-driving instructions are e cient for such vehicles. In this pilot study, participants (N=13) drove an instrumented vehicle (Toyota Camry 2007) with an automatic transmission. Fuel consumption of the participants was compared before and after they received simple eco-driving instructions. Participants drove the same vehicle on the same urban route under similar tra c conditions. We found that participants drove at similar speeds during their baseline and eco-friendly drives, and reduced the level of their accelerations and decelerations during eco-driving. Fuel consumption decreased for the complete drive by 7%, but not on the motorway and inclined sections of the study. Gas emissions were estimated with the VT-micro model, and emissions of the studied pollutants (CO2, CO, NOX and HC) were reduced, but no di erence was observed for CO2 on the motorway and inclined sections. The di erence for the complete lap is 3% for CO2. We have found evidence showing that simple eco-driving instructions are e cient in the case of automatic transmission in an urban environment, but towards the lowest values of the spectrum of fuel consumption reduction from the di erent eco-driving studies.

From science to management : using Bayesian networks to learn about Lyngbya

Toxic blooms of Lyngbya majuscula occur in coastal areas worldwide and have major ecological, health and economic consequences. The exact causes and combinations of factors which lead to these blooms are not clearly understood. Lyngbya experts and stakeholders are a particularly diverse group, including ecologists, scientists, state and local government representatives, community organisations, catchment industry groups and local fishermen. An integrated Bayesian Network approach was developed to better understand and model this complex environmental problem, identify knowledge gaps, prioritise future research and evaluate management options.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

Beyond compliance : project on an integrated systems approach for pest risk management in South East Asia

The Beyond Compliance project, which began in July 2011 with funding from the Standards and Trade Development Facility for 2 years, aims to enhance competency and confidence in the South East Asian sub-region by applying a Systems Approach for pest risk management. The Systems Approach involves the use of integrated measures, at least two of which are independent, that cumulatively reduce the risk of introducing exotic pests through trade. Although useful in circumstances where single measures are inappropriate or unavailable, the Systems Approach is inherently more complicated than single-measure approaches, which may inhibit its uptake. The project methodology is to take prototype decision-support tools, such as Control Point-Bayesian Networks (CP-BN), developed in recent plant health initiatives in other regions, including the European PRATIQUE project, and to refine them within this sub-regional context. Case studies of high-priority potential agricultural trade will be conducted by National Plant Protection Organizations of participating South East Asian countries in trials of the tools, before further modifications. Longer term outcomes may include: more robust pest risk management in the region (for exports and imports); greater inclusion of stakeholders in development of pest risk management plans; increased confidence in trade negotiations; and new opportunities for trade.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

What is an expert? A systems perspective on expertise

1. Expert knowledge continues to gain recognition as a valuable source of information in a wide range of research applications. Despite recent advances in defining expert knowledge, comparatively little attention has been given to how to view expertise as a system of interacting contributory factors, and thereby, to quantify an individual’s expertise. 2. We present a systems approach to describing expertise that accounts for many contributing factors and their interrelationships, and allows quantification of an individual’s expertise. A Bayesian network (BN) was chosen for this purpose. For the purpose of illustration, we focused on taxonomic expertise. The model structure was developed in consultation with professional taxonomists. The relative importance of the factors within the network were determined by a second set of senior taxonomists. This second set of experts (i.e. supra-experts) also provided validation of the model structure. Model performance was then assessed by applying the model to hypothetical career states in the discipline of taxonomy. Hypothetical career states were used to incorporate the greatest possible differences in career states and provide an opportunity to test the model against known inputs. 3. The resulting BN model consisted of 18 primary nodes feeding through one to three higher-order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra-experts for some nodes, but not others. The higher order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite differences in the node weights provided by our supra-experts, there was remarkably good agreement among assessments of our hypothetical experts that accurately reflected differences we had built into them. 4. This systems approach provides a novel way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Degradation of simazine from aqueous solutions by diatomite-supported nanosized zero-valent iron composite materials

A novel composite material based on deposition of nanosized zero-valent iron (nZVI) particles on acid-leached diatomite was synthesised for the removal of a chlorinated contaminant in water. The nZVI /diatomite composites were characterized by X-ray diffraction, scanning electron microscopy, elemental analysis, transmission electron microscopy and X-ray photoelectron spectroscopy. Compared with the pure nZVI particles, better dispersion of nZVI particles on the surface or inside the pores of diatom shells was observed. The herbicide simazine was selected as the model chlorinated contaminant and the removal efficiency by nZVI /diatomite composite was compared with that of the pristine nZVI and commercial iron powder. It was found that the diatomite supported nZVI composite material prepared by centrifugation exhibits relatively better efficient activity in decomposition of simazine than commercial Fe, lab synthesized nZVI and composite material prepared via rotary evaporation, and the optimum experimental conditions were obtained based on a series of batch experiments. This study on immobilizing nZVI particles onto diatomite opens a new avenue for the practical application of nZVI and the diatomite-supported nanosized zero-valent iron composite materials have potential applications in environmental remediation.

Age-related trends in urinary excretion of bisphenol A in Australian children and adults : evidence from a pooled sample study using samples of convenience

Bisphenol A (BPA or 4,4’-(propane-2,2-diyl)diphenol) is a chemical intermediate in the production of polycarbonate and epoxy resins, and used in a wide range of applications. BPA has attracted significant attention in the past decade due to its frequency of detection in human populations worldwide, demonstrated animal toxicity and potential impact on human health, particularly during critical periods of development. The aim of this study was to perform a preliminary assessment of age-related trends in urinary concentration and to estimate daily excretion of BPA in Australian children (aged (>0 – <5 years) and adults (≥15 – <75 years). This was achieved using 79 samples pooled by age and gender, created from 868 individual samples of convenience collected as part of routine, community-based pathology testing. Total BPA was analyzed using online-SPE-LC-MS/MS and detected in all samples with a range of 0.65 – 265 ng/ml. No significant differences were observed between males and females. A urine flow model was constructed from published values and used to provide an estimate of daily excretion per unit bodyweight for each pooled sample. The daily excretion estimates ranged from 26.2 – 18200 ng/kg-d for children; and 20.1 – 165 ng/kg-d for adults. Urinary concentrations and estimated excretion rates were inversely associated with age, and estimated daily excretion rates in infants and young children were significantly higher than in adults (geometric mean: 107 and 47.0 ng/kg-d, respectively). Higher excretion of BPA in children may be explained by their higher food consumption relative to body weight compared to adults and adolescents, and may also reflect alternative exposure pathways and sources. Keywords: bisphenol A, biomonitoring, children, urine flow, Australia

Evaluation framework for green procurement in road construction

Purpose Most barriers and enablers of sustainable projects are related to procurement. This study proposes a framework for evaluating green procurement practices throughout the lifecycle of road construction projects and demonstrates its application through an Australian case study. Design/methodology/approach The study is based on linking the phases of road construction with incentive mechanisms for proactively motivating behavioural change. A holistic view on utilised and potential incentives is attempted with a literature review and a state-of-practice review. The latter is based on interviews and 90 policy and procurement documents across five Australian states. Findings An evaluation framework with seven procurement stages is suggested to describe current state green procurement incentives throughout the delivery lifecycle of road construction projects. The Australian case study was found to provide useful data to identify gaps and strong points of the different states regarding their level of integration of sustainability and greenhouse gas emissions GHG) reduction elements in their procurement practices. This understanding was used to draw recommendations on future advancement of green procurement. Originality/value: Government entities across the globe can impact considerably the achievement of sustainability and GHG targets, by using their procurement practices and requirements to create incentives for contractors and suppliers to engage in more GHG conscious practices. The present study provides a systematic account of how green procurement practices can be underpinned using the Australian road construction industry as a case study, and distinguish between strong and weak links in the green procurement chain to draw recommendations for future initiatives.

Development of a computer based 1D-2D dynamic flood model. Case study of the Pagsangaan river basin in Leyte, the Philippines

Floods are among the most devastating events that affect primarily tropical, archipelagic countries such as the Philippines. With the current predictions of climate change set to include rising sea levels, intensification of typhoon strength and a general increase in the mean annual precipitation throughout the Philippines, it has become paramount to prepare for the future so that the increased risk of floods on the country does not translate into more economic and human loss. Field work and data gathering was done within the framework of an internship at the former German Technical Cooperation (GTZ) in cooperation with the Local Government Unit of Ormoc City, Leyte, The Philippines, in order to develop a dynamic computer based flood model for the basin of the Pagsangaan River. To this end, different geo-spatial analysis tools such as PCRaster and ArcGIS, hydrological analysis packages and basic engineering techniques were assessed and implemented. The aim was to develop a dynamic flood model and use the development process to determine the required data, availability and impact on the results as case study for flood early warning systems in the Philippines. The hope is that such projects can help to reduce flood risk by including the results of worst case scenario analyses and current climate change predictions into city planning for municipal development, monitoring strategies and early warning systems. The project was developed using a 1D-2D coupled model in SOBEK (Deltares Hydrological modelling software package) and was also used as a case study to analyze and understand the influence of different factors such as land use, schematization, time step size and tidal variation on the flood characteristics. Several sources of relevant satellite data were compared, such as Digital Elevation Models (DEMs) from ASTER and SRTM data, as well as satellite rainfall data from the GIOVANNI server (NASA) and field gauge data. Different methods were used in the attempt to partially calibrate and validate the model to finally simulate and study two Climate Change scenarios based on scenario A1B predictions. It was observed that large areas currently considered not prone to floods will become low flood risk (0.1-1 m water depth). Furthermore, larger sections of the floodplains upstream of the Lilo- an’s Bridge will become moderate flood risk areas (1 - 2 m water depth). The flood hazard maps created for the development of the present project will be presented to the LGU and the model will be used to create a larger set of possible flood prone areas related to rainfall intensity by GTZ’s Local Disaster Risk Management Department and to study possible improvements to the current early warning system and monitoring of the basin section belonging to Ormoc City; recommendations about further enhancement of the geo-hydro-meteorological data to improve the model’s accuracy mainly on areas of interest will also be presented at the LGU.