411 resultados para POLLUTION CONTROL

em Queensland University of Technology - ePrints Archive


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Willingness to pay models have shown the theoretical relationships between the contingent valuation, cost of illness and the avertive behaviour approaches. In this paper, field survey data are used to compare the relationships between these three approaches and to demonstrate that contingent valuation bids exceed the sum of cost of illness and the avertive behaviour approach estimates. The estimates provide a validity check for CV bids and further support the claim that contingent valuation studies are theoretically consistent.

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Though increased particulate air pollution has been consistently associated with elevated mortality, evidence regarding whether diminished particulate air pollution would lead to mortality reduction is limited. Citywide air pollution mitigation program during the 2010 Asian Games in Guangzhou, China, provided such an opportunity. Daily mortality from non-accidental, cardiovascular and respiratory diseases was compared for 51 intervention days (November 1–December 21) in 2010 with the same calendar date of baseline years (2006–2009 and 2011). Relative risk (RR) and 95% confidence interval (95% CI) were estimated using a time series Poisson model, adjusting for day of week, public holidays, daily mean temperature and relative humidity. Daily PM10 (particle with aerodynamic diameter less than 10 μm) decreased from 88.64 μg/m3 during the baseline period to 80.61 μg/m3 during the Asian Games period. Other measured air pollutants and weather variables did not differ substantially. Daily mortality from non-accidental, cardiovascular and respiratory diseases decreased from 32, 11 and 6 during the baseline period to 25, 8 and 5 during the Games period, the corresponding RR for the Games period compared with the baseline period was 0.79 (95% CI: 0.73–0.86), 0.77 (95% CI: 0.66–0.89) and 0.68 (95% CI: 0.57–0.80), respectively. No significant decreases were observed in other months of 2010 in Guangzhou and intervention period in two control cities. This finding supports the efforts to reduce air pollution and improve public health through transportation restriction and industrial emission control.

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This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

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With the rapid urbanization progress, water resources protection and water pollution control have become key problems of human environment construction and social sustainable development. Many countries, especially Australia, have mature experiences. Water Sensitive Urban Design (WSUD) is one of the successful strategies that is put forward under this global situation and helps releasing heavy environmental pressure from urbanization. The paper discussed main principles of WSUD and then took Shijiazhuang, Heibei and Yueng, Hunan for examples trying to apply WSUD in river landscape projects in China's new urban area, thus doing contributions to more sustainable water management in new urban areas in China.

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Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

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This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

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Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, enrichment factors and Principal Component Analysis –Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay.

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This study developed a comprehensive research methodology for identification and quantification of sources responsible for pollutant build-up and wash-off from urban road surfaces. The study identified soil and asphalt wear, and non-combusted diesel fuel as the most influential sources for metal and hydrocarbon pollution respectively. The study also developed mathematical models to relate contributions from identified sources to underlying site specific factors such as land use and traffic. Developed mathematical model will play a key role in urban planning practices, enabling the implementation of effective water pollution control strategies.

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Polycyclic Aromatic Hydrocarbons (PAHs) represent a major class of toxic pollutants because of their carcinogenic and mutagenic characteristics. People living in urban areas are regularly exposed to PAHs because of abundance of their emission sources. Within this context, this study aimed to: (i) identify and quantify the levels of ambient PAHs in an urban environment; (ii) evaluate their toxicity; and (iii) identify their sources as well as the contribution of specific sources to measured concentrations. Sixteen PAHs were identified and quantified in air samples collected from Brisbane. Principal Component Analysis – Absolute Principal Component Scores (PCA- APCS) was used in order to conduct source apportionment of the measured PAHs. Vehicular emissions, natural gas combustion, petrol emissions and evaporative/unburned fuel were the sources identified; contributing 56%, 21%, 15% and 8% of the total PAHs emissions, respectively, all of which need to be considered for any pollution control measures implemented in urban areas.

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Background, Aim and Scope The impact of air pollution on school children’s health is currently one of the key foci of international and national agencies. Of particular concern are ultrafine particles which are emitted in large quantities, contain large concentrations of toxins and are deposited deeply in the respiratory tract. Materials and methods In this study, an intensive sampling campaign of indoor and outdoor airborne particulate matter was carried out in a primary school in February 2006 to investigate indoor and outdoor particle number (PN) and mass concentrations (PM2.5), and particle size distribution, and to evaluate the influence of outdoor air pollution on the indoor air. Results For outdoor PN and PM2.5, early morning and late afternoon peaks were observed on weekdays, which are consistent with traffic rush hours, indicating the predominant effect of vehicular emissions. However, the temporal variations of outdoor PM2.5 and PN concentrations occasionally showed extremely high peaks, mainly due to human activities such as cigarette smoking and the operation of mower near the sampling site. The indoor PM2.5 level was mainly affected by the outdoor PM2.5 (r = 0.68, p<0.01), whereas the indoor PN concentration had some association with outdoor PN values (r = 0.66, p<0.01) even though the indoor PN concentration was occasionally influenced by indoor sources, such as cooking, cleaning and floor polishing activities. Correlation analysis indicated that the outdoor PM2.5 was inversely correlated with the indoor to outdoor PM2.5 ratio (I/O ratio) (r = -0.49, p<0.01), while the indoor PN had a weak correlation with the I/O ratio for PN (r = 0.34, p<0.01). Discussion and Conclusions The results showed that occupancy did not cause any major changes to the modal structure of particle number and size distribution, even though the I/O ratio was different for different size classes. The I/O curves had a maximum value for particles with diameters of 100 – 400 nm under both occupied and unoccupied scenarios, whereas no significant difference in I/O ratio for PM2.5 was observed between occupied and unoccupied conditions. Inspection of the size-resolved I/O ratios in the preschool centre and the classroom suggested that the I/O ratio in the preschool centre was the highest for accumulation mode particles at 600 nm after school hours, whereas the average I/O ratios of both nucleation mode and accumulation mode particles in the classroom were much lower than those of Aitken mode particles. Recommendations and Perspectives The findings obtained in this study are useful for epidemiological studies to estimate the total personal exposure of children, and to develop appropriate control strategies for minimizing the adverse health effects on school children.

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This latest briefing by Professor Reece Walters in the What is crime? series, draws attention to an area of harm that is often absent from criminological debate. He highlights the human costs of air pollution and failed attempts to adequately regulate and control such harm. Arguing for a cross disciplinary ‘eco-crime’ narrative, the author calls for greater understanding of the far-reaching consequences of air pollution which could set in train changes which may lead to a ‘more robust and meaningful system of justice’. Describing current arrangements in place to control and regulate air pollution, Walters draws attention to the lack of neutrality in current arrangements and the bias ‘towards the economic imperatives of free trade over and above the centrality of environmental protection’. While attention is often given to direct and individualised instances of ‘crime’, the serious consequences of air pollution are frequently neglected. The negative effects of pollution on health and well-being are often borne by people already experiencing a range of other disadvantages. In a global and national context, it is often the poor who are affected most. Ultimately, political and economic imperatives have historically helped to shape legal and regulatory regimes. Whether this is an inherent flaw in current systems or something that can be overcome in favour of dealing with more wide-ranging harms is an area that requires further discussion and debate.

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Exposure to air pollution during pregnancy is a potential cause of adverse birth outcomes such as preterm birth and stillbirth. The risk of exposure may be greater during vulnerable windows of the pregnancy which might only be weeks long. We demonstrate a method to find these windows based on smoothing the risk of weekly exposure using conditional autoregression. We use incidence density sampling to match cases with adverse birth outcomes to controls whose gestation lasted at least as long as the case. This matching means that cases and controls are have equal length exposure periods, rather than comparing, for example, cases with short gestations to controls with longer gestations. We demonstrate the ability of the method to find vulnerable windows using two simulation studies. We illustrate the method by examining the association between particulate matter air pollution and stillbirth in Brisbane, Australia.

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The international legal regime on shipbreaking is in its formative years. At the international level, the shipbreaking industry is partially governed by the Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and their Disposal. However, how far this convention will be applicable for all aspects of transboundary movement of end-of-life ships is still, at least in the view of some scholars, a debatable issue. Against this backdrop, the International Maritime Organisation (IMO) has adopted a new, legally binding convention for shipbreaking. There is a rising voice from the developing countries that the convention is likely to impose more obligations on recycling facilities in the developing countries than on shipowners from rich nations. This may be identified as a clear derogation from the globally recognized international environmental law principle of common but differentiated treatment. This article will examine in detail major international conventions regulating transboundary movement and environmentally sound disposal of obsolete ships, as well as the corresponding laws of Bangladesh for implementing these conventions in the domestic arena. Moreover this article will examine in detail the recently adopted IMO Ship Recycling Convention.

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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.