Port of Brisbane stormwater quality : stage 2 development of a port specific water quality model

Background: The quality of stormwater runoff from ports is significant as it can be an important source of pollution to the marine environment. This is also a significant issue for the Port of Brisbane as it is located in an area of high environmental values. Therefore, it is imperative to develop an in-depth understanding of stormwater runoff quality to ensure that appropriate strategies are in place for quality improvement, where necessary. To this end, the Port of Brisbane Corporation aimed to develop a port specific stormwater model for the Fisherman Islands facility. The need has to be considered in the context of the proposed future developments of the Port area. ----------------- The Project: The research project is an outcome of the collaborative Partnership between the Port of Brisbane Corporation (POBC) and Queensland University of Technology (QUT). A key feature of this Partnership is that it seeks to undertake research to assist the Port in strengthening the environmental custodianship of the Port area through ‘cutting edge’ research and its translation into practical application. ------------------ The project was separated into two stages. The first stage developed a quantitative understanding of the generation potential of pollutant loads in the existing land uses. This knowledge was then used as input for the stormwater quality model developed in the subsequent stage. The aim is to expand this model across the yet to be developed port expansion area. This is in order to predict pollutant loads associated with stormwater flows from this area with the longer term objective of contributing to the development of ecological risk mitigation strategies for future expansion scenarios. ----------------- Study approach: Stage 1 of the overall study confirmed that Port land uses are unique in terms of the anthropogenic activities occurring on them. This uniqueness in land use results in distinctive stormwater quality characteristics different to other conventional urban land uses. Therefore, it was not scientifically valid to consider the Port as belonging to a single land use category or to consider as being similar to any typical urban land use. The approach adopted in this study was very different to conventional modelling studies where modelling parameters are developed using calibration. The field investigations undertaken in Stage 1 of the overall study helped to create fundamental knowledge on pollutant build-up and wash-off in different Port land uses. This knowledge was then used in computer modelling so that the specific characteristics of pollutant build-up and wash-off can be replicated. This meant that no calibration processes were involved due to the use of measured parameters for build-up and wash-off. ---------------- Conclusions: Stage 2 of the study was primarily undertaken using the SWMM stormwater quality model. It is a physically based model which replicates natural processes as closely as possible. The time step used and catchment variability considered was adequate to accommodate the temporal and spatial variability of input parameters and the parameters used in the modelling reflect the true nature of rainfall-runoff and pollutant processes to the best of currently available knowledge. In this study, the initial loss values adopted for the impervious surfaces are relatively high compared to values noted in research literature. However, given the scientifically valid approach used for the field investigations, it is appropriate to adopt the initial losses derived from this study for future modelling of Port land uses. The relatively high initial losses will reduce the runoff volume generated as well as the frequency of runoff events significantly. Apart from initial losses, most of the other parameters used in SWMM modelling are generic to most modelling studies. Development of parameters for MUSIC model source nodes was one of the primary objectives of this study. MUSIC, uses the mean and standard deviation of pollutant parameters based on a normal distribution. However, based on the values generated in this study, the variation of Event Mean Concentrations (EMCs) for Port land uses within the given investigation period does not fit a normal distribution. This is possibly due to the fact that only one specific location was considered, namely the Port of Brisbane unlike in the case of the MUSIC model where a range of areas with different geographic and climatic conditions were investigated. Consequently, the assumptions used in MUSIC are not totally applicable for the analysis of water quality in Port land uses. Therefore, in using the parameters included in this report for MUSIC modelling, it is important to note that it may result in under or over estimations of annual pollutant loads. It is recommended that the annual pollutant load values given in the report should be used as a guide to assess the accuracy of the modelling outcomes. A step by step guide for using the knowledge generated from this study for MUSIC modelling is given in Table 4.6. ------------------ Recommendations: The following recommendations are provided to further strengthen the cutting edge nature of the work undertaken: * It is important to further validate the approach recommended for stormwater quality modelling at the Port. Validation will require data collection in relation to rainfall, runoff and water quality from the selected Port land uses. Additionally, the recommended modelling approach could be applied to a soon-to-be-developed area to assess ‘before’ and ‘after’ scenarios. * In the modelling study, TSS was adopted as the surrogate parameter for other pollutants. This approach was based on other urban water quality research undertaken at QUT. The validity of this approach should be further assessed for Port land uses. * The adoption of TSS as a surrogate parameter for other pollutants and the confirmation that the <150 m particle size range was predominant in suspended solids for pollutant wash-off gives rise to a number of important considerations. The ability of the existing structural stormwater mitigation measures to remove the <150 m particle size range need to be assessed. The feasibility of introducing source control measures as opposed to end-of-pipe measures for stormwater quality improvement may also need to be considered.

Improved functional ability and independence in activities of daily living for older adults at high risk of hospital readmission : a randomised controlled trial

Objective: During hospitalisation older people often experience functional decline which impacts on their future independence. The objective of this study was to evaluate a multifaceted transitional care intervention including home-based exercise strategies for at-risk older people on functional status, independence in activities of daily living, and walking ability. Methods: A randomised controlled trial was undertaken in a metropolitan hospital in Australia with 128 patients (64 intervention, 64 control) aged over 65 years with an acute medical admission and at least one risk factor for hospital readmission. The intervention group received an individually tailored program for exercise and follow-up care which was commenced in hospital and included regular visits in hospital by a physiotherapist and a Registered Nurse, a home visit following discharge, and regular telephone follow-up for 24 weeks following discharge. The program was designed to improve health promoting behaviours, strength, stability, endurance and mobility. Data were collected at baseline, then 4, 12 and 24 weeks following discharge using the Index of Activities of Daily Living (ADL), Instrumental Index of Activities of Daily Living (IADL), and the Walking Impairment Questionnaire (Modified). Results: Significant improvements were found in the intervention group in IADL scores (p<.001), ADL scores (p<.001), and WIQ scale scores (p<.001) in comparison to the control group. The greatest improvements were found in the first four weeks following discharge. Conclusions: Early introduction of a transitional model of care incorporating a tailored exercise program and regular telephone follow-up for hospitalised at-risk older adults can improve independence and functional ability.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Testing a belief-based intervention encouraging sun safety among adolescents in a high risk area

Objective. To provide a preliminary test of a Theory of Planned Behavior (TPB) belief-based intervention to increase adolescents’ sun protective behaviors in a high risk area, Queensland, Australia. Methods. In the period of October-November, 2007 and May-June, 2008, 80 adolescents (14.53 ± 0.69 years) were recruited from two secondary schools (one government and one private) in Queensland after obtaining student, parental, and school informed consent. Adolescents were allocated to either a control or intervention condition based on the class they attended. The intervention comprised three, one hour in-school sessions facilitated by Cancer Council Queensland employees with sessions covering the belief basis of the TPB (i.e., behavioral, normative, and control [barrier and motivator] sun-safe beliefs). Participants completed questionnaires assessing sun-safety beliefs, intentions, and behavior pre- and post-intervention. Repeated Measures Multivariate Analysis of Variance was used to test the effect of the intervention across time on these constructs. Results. Students completing the intervention reported stronger sun-safe normative and motivator beliefs and intentions and the performance of more sun-safe behaviors across time than those in the control condition. Conclusion. Strengthening beliefs about the approval of others and motivators for sun protection may encourage sun-safe cognitions and actions among adolescents.

Safety impacts of alcohol and other drugs in the construction industry : a research methodology

Anecdotal evidence from the infrastructure and building sectors highlights issues of drugs and alcohol and its association with safety risk on construction sites. Operating machinery and mobile equipment, proximity to live traffic together with congested sites, electrical equipment and operating at heights conspire to accentuate the potential adverse impact of drugs and alcohol in the workplace. While most Australian jurisdictions have identified this as a critical safety issue, information is limited regarding the prevalence of alcohol and other drugs in the workplace and there is limited evidential guidance regarding how to effectively and efficiently address such an issue. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgement from drugs and alcohol. A nationally consistent collaborative approach across the construction workforce - involving employers and employees; clients; unions; contractors and sub-contractors is required to engender a cultural change in the construction workforce – in a similar manner to the on-going initiative in securing a cultural change to drink-driving in our society where peer intervention and support is encouraged. This study has four key objectives. Firstly, using the standard World Health Organisation AUDIT, a national qualitative and quantitative assessment of the use of drugs and alcohol will be carried out. This will build upon similar studies carried out in the Australian energy and mining sectors. Secondly, the development of an appropriate industry policy will adopt a non-punitive and rehabilitative approach developed in consultation with employers and employees across the infrastructure and building sectors, with the aim it be adopted nationally for adoption at the construction workplace. Thirdly, an industry-specific cultural change management program will be developed through a nationally collaborative approach to reducing the risk of impaired performance on construction sites and increasing workers’ commitment to drugs and alcohol safety. Finally, an implementation plan will be developed from data gathered from both managers and construction employees. Such an approach stands to benefit not only occupational health and safety, through a greater understanding of the safety impacts of alcohol and other drugs at work, but also alcohol and drug use as a wider community health issue. This paper will provide an overview of the background and significance of the study as well as outlining the proposed methodology that will be used to evaluate the safety impacts of alcohol and other drugs in the construction industry.

Organisational challenges in understanding and implementing effective buiness continuity management strategies in a complex and critical organisation : an airport case study

With the increasing complexity of modern day threats and the growing sophistication of interlinked and interdependent operating environments, Business Continuity Management (BCM) has emerged as a new discipline, offering a strategic approach to safeguarding organisational functions. Of significant interest is the application of BCM frameworks and strategies within critical infrastructure, and in particular the aviation industry. Given the increased focus on security and safety for critical infrastructures, research into the adoption of BCM principles within an airport environment provides valuable management outcomes and research into a previously neglected area of inquisition. This research has used a single case study methodology to identify possible impediments to BCM adoption and implementation by the Brisbane Airport Corporation (BAC). It has identified a number of misalignments between the required breadth of focus for a BCM program, identified differing views on specific roles and responsibilities required during a major disruptive event and illustrated the complexities of the Brisbane Airport which impede the understanding and implementation of effective Business Continuity Management Strategies.