Heat-related morbidity in Brisbane, Australia : spatial variation and area-level predictors

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

20 Years of pacifying responses to environmental management

Using a state, pressure, response framework, we provide an evidence-based reflection on environmental outcomes in Australia and New Zealand across the domains of climate change, biodiversity, freshwater and marine management, emphasising the role of Indigenous and business perspectives. Significant developments have occurred in the past 20 years through affirmation of Indigenous rights and responsibilities. Responses to climate change have tended to emphasise passive risk management with unclear outcomes. Despite meeting biodiversity protection targets, outcomes are worsening, suggesting a need to challenge the dualistic preservation/production land categorisations. In freshwater and marine management, a mix of collaborative and market-based responses has emerged, although their efficacy remains untested. A reliance on voluntary approaches by business makes critical assessment of progress difficult. Thus, despite strong progress in some areas, the adaptiveness of environmental management remains limited, and many indicators suggest continuing decline in environmental condition. Our responses have been largely pacifying in nature, leading to perverse outcomes and failure to acknowledge alternatives that might address deteriorating environmental conditions. A shift is needed towards deliberative policy experimentation that truly values the application of novel and diversified approaches and facilitates integrated learning across environmental domains.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

Markers of genetic susceptibility in human environmental hygiene and toxicology : the role of selected CYP, NAT and GST genes

Inherited genetic traits co-determine the susceptibility of an individual to a toxic chemical. Special emphasis has been put on individual responses to environmental and industrial carcinogens, but other chronic diseases are of increasing interest. Polymorphisms of relevant xenobiotic metabolising enzymes may be used as toxicological susceptibility markers. A growing number of genes encoding enzymes involved in biotransformation of toxicants and in cellular defence against toxicant-induced damage to the cells has been identified and cloned, leading to increased knowledge of allelic variants of genes and genetic defects that may result in a differential susceptibility toward environmental toxicants. "Low penetrating" polymorphisms in metabolism genes tend to be much more common in the population than allelic variants of "high penetrating" cancer genes, and are therefore of considerable importance from a public health point of view. Positive associations between cancer and CYP1A1 alleles, in particular the *2C I462V allele, were found for tissues following the aerodigestive tract. Again, in most cases, the effect of the variant CYP1A1 allele becomes apparent or clearer in connection with the GSTM1 null allele. The CYP1B1 codon 432 polymorphism (CYP1B1*3) has been identified as a susceptibility factor in smoking-related head-and-neck squameous cell cancer. The impact of this polymorphic variant of CYP1B1 on cancer risk was also reflected by an association with the frequency of somatic mutations of the p53 gene. Combined genotype analysis of CYP1B1 and the glutathione transferases GSTM1 or GSTT1 has also pointed to interactive effects. Of particular interest for the industrial and environmental field is the isozyme CYP2E1. Several genotypes of this isozyme have been characterised which seem to be associated with different levels of expression of enzyme activity. The acetylator status for NAT2 can be determined by genotyping or by phenotyping. In the pathogenesis of human bladder cancer due to occupational exposure to "classical" aromatic amines (benzidine, 4-aminodiphenyl, 1-naphthylamine) acetylation by NAT2 is regarded as a detoxication step. Interestingly, the underlying European findings of a higher susceptibility of slow acetylators towards aromatic amines are in contrast to findings in Chinese workers occupationally exposed to aromatic amines which points to different mechanisms of susceptibility between European and Chinese populations. Regarding human bladder cancer, the hypothesis has been put forward that genetic polymorphism of GSTM1 might be linked with the occurrence of this tumour type. This supports the hypothesis that exposure to PAH might causally be involved in urothelial cancers. The human polymorphic GST catalysing conjugation of halomethanes, dihalomethanes, ethylene oxide and a number of other industrial compounds could be characterised as a class theta enzyme (GSTT1) by means of molecular biology. "Conjugator" and "non-conjugator" phenotypes are coincident with the presence and absence of the GSTT1 gene. There are wide variations in the frequencies of GSTT1 deletion (GSTT1 *0/0) among different ethnicities. Human phenotyping is facilitated by the GST activity towards methyl bromide or ethylene oxide in erythrocytes which is representative of the metabolic GSTT1 competence of the entire organism. Inter-individual variations in xenobiotic metabolism capacities may be due to polymorphisms of the genes coding for the enzymes themselves or of the genes coding for the receptors or transcription factors which regulate the expression of the enzymes. Also, polymorphisms in several regions of genes may cause altered ligand affinity, transactivation activity or expression levels of the receptor subsequently influencing the expression of the downstream target genes. Studies of individual susceptibility to toxicants and gene-environment interaction are now emerging as an important component of molecular epidemiology.

Genetic susceptibility to environmental toxicants : the interface between human and experimental studies in the development of new toxicological concepts

The growing knowledge of the genetic polymorphisms of enzymes metabolising xenobiotics in humans and their connections with individual susceptibility towards toxicants has created new and important interfaces between human epidemiology and experimental toxicology. The results of molecular epidemiological studies may provide new hypotheses and concepts, which call for experimental verification, and experimental concepts may obtain further proof by molecular epidemiological studies. If applied diligently, these possibilities may be combined to lead to new strategies of human-oriented toxicological research. This overview will present some outstanding examples for such strategies taken from the practically very important field of occupational toxicology. The main focus is placed on the effects of enzyme polymorphisms of the xenobiotic metabolism in association with the induction of bladder cancer and renal cell cancer after exposure to occupational chemicals. Also, smoking and induction of head and neck squamous cell cancer are considered.

Differential effects of monotony versus fatigue on driving performance and the effectiveness of various detection methods : implications for road safety in the ACT

Background Situational driving factors, including fatigue, distraction, inattention and monotony, are recognised killers in Australia, contributing to an estimated 40% of fatal crashes and 34% of all crashes . More often than not the main contributing factor is identified as fatigue, yet poor driving performance has been found to emerge early in monotonous conditions, independent of fatigue symptoms and time on task. This early emergence suggests an important role for monotony. However, much road safety research suggests that monotony is solely a task characteristic that directly causes fatigue and associated symptoms and there remains an absence of consistent evidence explaining the relationship. Objectives We report an experimental study designed to disentangle the characteristics and effects of monotony from those associated with fatigue. Specifically, we examined whether poor driving performance associated with hypovigilance emerges as a consequence of monotony, independent of fatigue. We also examined whether monotony is a multidimensional construct, determined by environmental characteristics and/or task demands that independently moderate sustained attention and associated driving performance. Method Using a driving simulator, participants completed four, 40 minute driving scenarios. The scenarios varied in the degree of monotony as determined by the degree of variation in road design (e.g., straight roads vs. curves) and/or road side scenery. Fatigue, as well as a number of other factors known to moderate vigilance and driving performance, was controlled for. To track changes across time, driving performance was assessed in five minute time periods using a range of behavioural, subjective and physiological measures, including steering wheel movements, lane positioning, electroencephalograms, skin conductance, and oculomotor activity. Results Results indicate that driving performance is worse in monotonous driving conditions characterised by low variability in road design. Critically, performance decrements associated with monotony emerge very early, suggesting monotony effects operate independent of fatigue. Conclusion Monotony is a multi-dimensional construct where, in a driving context, roads containing low variability in design are monotonous and those high in variability are non-monotonous. Importantly, low variability in road side scenery does not appear to exacerbate monotony or associated poor performance. However, high variability in road side scenery can act as a distraction and impair sustained attention and poor performance when driving on monotonous roads. Furthermore, high sensation seekers seem to be more susceptible to distraction when driving on monotonous roads. Implications of our results for the relationship between monotony and fatigue, and the possible construct-specific detection methods in a road safety context, will be discussed.

Geochemistry-based coral palaeoclimate studies and the potential of ‘non-traditional’ (non-massive Porites) corals : recent developments and future progression

Understanding the natural variability of the Earth's climate system and accurately identifying potential anthropogenic influences requires long term, geographically distributed records of key climate indicators, such as temperature and precipitation that extend prior to the last 400. years of the Holocene. Reef corals provide an excellent source of high resolution climate records, and importantly represent the tropical marine environment where palaeoclimate data are urgently required. Recent decades have seen significant improvement in our understanding of coral biomineralisation, the associated uptake of geochemical proxies and methods of identifying and understanding the effects of both early and late, post depositional diagenetic alteration. These processes all have significant implications for interpreting geochemical proxies relevant to palaeoclimatic reconstructions. This paper reviews the current 'state of the art' in terms of coral based palaeoclimate reconstructions and highlights a key remaining problem. The majority of coral based palaeoclimate research has been derived from massive colonies of Porites. However, massive Porites are not globally abundant and may not provide material of a particular age of interest in those regions where they are present. Therefore, there is great potential for alternate coral genera to act as complimentary climate archives. While it remains critical to consider five key factors - vital effects, differential growth morphologies, geochemical heterogeneity in the skeletal ultrastructure, transfer equation selection and diagenetic screening of skeletal material - in order to allow the highest level of accuracy in coral palaeoclimate reconstructions, it is also important to develop alternate taxa for palaeoclimate studies in regions where Porites colonies are absent or rare. Currently as many as nine genera other than Porites have proven at least limited utility in palaeothermometry, most of which are found in the Atlantic/Caribbean region where massive Porites do not exist. Even branching taxa such as Acropora have significant potential to preserve environmental archives. Increasing this capability will greatly expand the number of potential geochemical archives available for longer term temporal records of palaeoclimate.

Investigations on road noise level spatial variability within a specially designed acoustic balcony

An investigation into the spatial distribution of road traffic noise levels on a balcony is conducted. A balcony constructed to a special acoustic design due to its elevation above an 8 lane motorway is selected for detailed measurements. The as-constructed balcony design includes solid parapets, side walls, ceiling shields and highly absorptive material placed on the ceiling. Road traffic noise measurements are conducted spatially using a five channel acoustic analyzer, where four microphones are located at various positions within the balcony space and one microphone placed outside the parapet at a reference position. Spatial distributions in both vertical and horizontal planes are measured. A theoretical model and prediction configuration is presented that assesses the acoustic performance of the balcony under existing traffic flow conditions. The prediction model implements a combined direct path, specular reflection path and diffuse reflection path utilizing image source and radiosity techniques. Results obtained from the prediction model are presented and compared to the measurement results. The predictions are found to correlate well with measurements with some minor differences that are explained. It is determined that the prediction methodology is acceptable to assess a wider range of street and balcony configuration scenarios.

Use of contract models to improve environmental outcomes in transport infrastructure construction

The type of contract model may have a significant influence on achieving project objectives, including environmental and climate change goals. This research investigates non-standard contract models impacting greenhouse gas emissions (GHG) in transport infrastructure construction in Australia. The research is based on the analysis of two case studies: an Early Contractor Involvement (ECI) contract and a Design and Construct (D&C) contract with GHG reduction requirements embedded in the contractor selection. Main findings support the use of ECIs for better integrating decisions made during the planning phase with the construction activities, and improve environmental outcomes while achieving financial and time savings. Key words: greenhouse gases reduction; road construction; contracting; ECI; D&C

Practical analysis of big acoustic sensor data for environmental monitoring

Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem; the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.