117 resultados para Municipal environmental management


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There is considerable scientific interest in personal exposure to ultrafine particles. Owing to their small size, these particles are able to penetrate deep into the lungs, where they may cause adverse respiratory, pulmonary and cardiovascular health effects. This article presents Bayesian hierarchical models for estimating and comparing inhaled particle surface area in the lung.

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Animals are often used as symbols in policy debates and media accounts of marine pollution. Images of miserable oil-soaked marine birds and mammals are prominent following high profile oil spills such as the Exxon Valdez, Prestige and Pacific Adventurer incidents. Portrayed as hapless victims, these animal actors are not only cast as powerful symbols of the effects of anthropogenic pollution but also represent an environment in crisis. Animals, like the broader environment, are seen as something which is acted upon. Less attention has been given to the ways in which animals have been cast as either the cause of marine pollution or as having the potential to actively mitigate the potential impacts of anthropogenic marine pollution. This article explores how animals are constructed with respect to vessel-sourced sewage pollution. Through a process of interpretive policy analysis, drawing on media reports and responses to an Australian regulatory review process this study found that, when defending the perceived right to pollute recreational boaters implicated animals such as dogs, fish, turtles, dolphins and seabirds in their pollution discourses. Scapegoating was an important rhetorical feature of claims-making strategies designed to avoid responsibility for changing sewage disposal practices.

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The relationship between corporate and sustainability performance continues to be controversial and unclear, not withstanding numerous theoretical and empirical studies. Despite this, views on corporate responsibilities “meet where management can show how voluntary social and environmental management contributes to the competitiveness and economic success of the company.” This approach is fundamental to the business case for infrastructure sustainability. It suggests that beyond-compliance activities undertaken by companies are commercially justified if they can be shown to contribute to profitability and shareholder value. Potential public good benefits range across a wide spectrum of economic (for example employment, local purchasing, reduced demand for electricity generation), social (indigenous employment and development, equity of access), and environmental (lower greenhouse gas emission, reduced use of non-renewable resources and potable water, less waste, enhanced biodiversity). Some of these benefits have impacts that lie in more than one of the economic, social, and environmental areas of public goods. Using a sustainability rating schemes and potential business benefits from sustainability initiatives, this paper presents a brief summary of an online survey of industry that identifies how rating scheme themes and business benefits relate. This allows for a case to be built demonstrating which sustainability themes offer particular business benefits.

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Ripening period refers to a phase of stabilization in sand filters in water treatment systems that follows a new installation or cleaning of the filter. Intermittent wetting and drying, a unique property of stormwater biofilters, would similarly be subjected to a phase of stabilization. Suspended solids, is an important parameter that is often used to monitor the stabilization of sand filters in water treatment systems. Stormwater biofilters however, contain organic material that is added to the filter layer to enhance nitrate removal, the dynamics of which is seldom analysed in stabilization of stormwater biofilters. Therefore, in this study of stormwater biofiltration in addition to suspended solids (Turbidity), organic matter (TOC, DOC, TN and TKN) was also monitored as a parameter for stabilization of the stormwater biofilter. One Perspex bioretention column (94 mm internal diameter) was fabricated with filter layer that contained 8% organic material and fed with tapwater with different antecedent dry days (0 – 40 day) at 100 mL/min. Samples were collected from the outflow at different time intervals between 2 – 150 minutes and were tested for Total Organic Carbon, Dissolved Organic Carbon, Total Nitrogen, Total Kjeldhal Nitrogen and Turbidity. The column was observed to experience two phases of stabilization, one at the beginning of each event that lasted for 30 minutes while the other phase was observed across subsequent events that related to the age of filter.

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The study examines the property value impacts of an announcement of a project which has potential environmental impacts as distinct from other studies that address costs associated with under-construction and the operating impacts of developments. The hypothesis is that the announcement of a proposed project with potential environmental impact creates uncertainty in the property market of the affected area, and this impact is greater on properties closer to the project than those farther from it. The results of the study confirm the hypothesis and indicate that the marginal willingness to pay for properties within a 5 km distance declined by AU$17,020 per km proximity to the proposed heavy vehicle route, after the proposed route was announced. The results support the need for more holistic measurement of cost–benefit analysis of projects and provide a basis for improved consideration by policy makers of the rights of affected parties.

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Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

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The relationship between governance arrangements and sustainability planning outcomes in complex governance systems remains poorly understood, despite significant discussions of governance in the environmental management literature emerging in the last decade. In order to analyse and examine the relationship between the health of sustainability planning governance and decision-making outcomes, this paper applies the Governance Systems Analysis framework (GSA) in the Cairns region. This paper analyses the sustainability planning governance arrangements in the Cairns region by exploring the capacity, connectivity and knowledge use of institutions in the region to deliver desired sustainability planning outcomes. The paper finds that the planning for sustainability in the Cairns region is on a knife’s edge, and could fail or succeed to deliver its intended decision-making outcomes. The paper concludes with recommendations for governance reform for sustainability in the Cairns region.

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The coal seam gas (CSG) industry is globally of potentially great importance economically. This study exemplifies the complex relationship between land use and management, groundwater impact and associated water treatment especially in relation to Queensland where a significant increase in the amount of gas extracted over the past 6 years has occurred. In order to effectively manage the environmental impact of the CSG industry it is necessary to appropriately understand the nature of the gas deposits, methods for gas collection, the physicochemical composition of the by-product associated water and the technologies available for water remediation. Australia is mainly considered arid and semi-arid and thus there is a need to not only beneficially reuse water resources but also protect existing ground water reservoirs such as the Great Artesian Basin (GAB). This paper focussed primarily on the Surat Basin located in Queensland and northern New South Wales. The mechanism for CSG formation, relation to local geological features, extraction approach and the potential impact/benefits of associated water was discussed. An outline of the current legislative requirements on physical and chemical properties of associated water in the Surat Basin was also provided, as well as the current treatment technologies used by the major CSG companies. This review was of significance in relation to the formulation of the most appropriate and cost effective management of associated water, while simultaneously preserving existing water resources and the environment.

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We report on ongoing research to develop a design theory for classes of information systems that allow for work practices that exhibit a minimal harmful impact on the natural environment. We call such information systems Green IS. In this paper we describe the building blocks of our Green IS design theory, which develops prescriptions for information systems that allow for: (1) belief formation, action formation and outcome measurement relating to (2) environmentally sustainable work practices and environmentally sustainable decisions on (3) a macro or micro level. For each element, we specify structural features, symbolic expressions, user abilities and goals required for the affordances to emerge. We also provide a set of testable propositions derived from our design theory and declare two principles of implementation.

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Ecosystem based management requires the integration of various types of assessment indicators. Understanding stakeholders' information preferences is important, in selecting those indicators that best support management and policy. Both the preferences of decision-makers and the general public may matter, in democratic participatory management institutions. This paper presents a multi-criteria analysis aimed at quantifying the relative importance to these groups of economic, ecological and socio-economic indicators usually considered when managing ecosystem services in a coastal development context. The Analytic Hierarchy Process (AHP) is applied within two nationwide surveys in Australia, and preferences of both the general public and decision-makers for these indicators are elicited and compared. Results show that, on average across both groups, the priority in assessing a generic coastal development project is for the ecological assessment of its impacts on marine biodiversity. Ecological assessment indicators are globally preferred to both economic and socio-economic indicators regardless of the nature of the impacts studied. These results are observed for a significantly larger proportion of decision-maker than general public respondents, questioning the extent to which the general public's preferences are well reflected in decision-making processes.

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Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

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This article examines sustainability disclosures by the major banks in the Asia-Pacific region (the six largest banks from each of four countries: Australia, Japan, China and India) during the period 2005 to 2012. The findings show sustainability disclosures by banks that participate in the global reporting initiative (GRI) are significantly higher than disclosures by those banks that have not participated in the GRI. Amongst those banks that have participated in the GRI there is is a higher rate of disclosure by externally assured banks than by non-externally assured banks. Among the GRI