883 resultados para Air quality management.


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The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

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The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

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Within the supply chain, the customer does not simply buy parts or services from suppliers, but also buys supplier capabilities, which results in quality products and services. Having a tool that handles the Inspection as well as the Nonconformance, Complaint, Corrective Action and Concession processes is key to successfully track the supplier performance. Taking as a case study a Supplier Quality Management (SQM) currently in operation in an Original Equipment Manufacturer (OEM) for automotive industry, this paper presents a platform to support a Supplier Quality Management System (SQMS), that fits the technical specification ISO/TS 16949 requirements. This prototype is composed by a web platform and a mobile App, having flexibility and mobility as key main characteristics.

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The purpose of this project was to investigate student learning in the areas of earth science and environmental responsibility using the subject of coal fires. Eastern Kentucky, where this study was performed, has several coal fires burning that affect the local air quality and may also affect the health of people living near them. This study was conducted during the regular education of 9th grade Earth Science classroom in Russell Independent Schools, located in Russell, Kentucky. Students conducted internet research, read current articles on the subject of coal fire emissions and effect on local ecology, and demonstrated what they learned through summative assessments. There were several aspects of coalmines and coal fires that students studied. Students were able to take this knowledge and information and use it as a learning tool to gain a better understanding of their own environment. Using the local history and geology of coalmines, along with the long tradition of mine production, was a very beneficial starting point, allowing students to learn about environmental impact, stewardship of their local environment, and methods of preserving and protecting the ecosystem.

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Indoor environmental conditions in classrooms, in particular temperature and indoor air quality, influence students’ health, attitude and performance. In recent years, several studies regarding indoor environmental quality of classrooms were published and natural ventilation proved to have great potential, particularly in southern European climate. This research aimed to evaluate indoor environmental conditions in eight schools and to assess their improvement potential by simple natural ventilation strategies. Temperature, relative humidity and carbon dioxide concentration were measured in 32 classrooms. Ventilation performance of the classrooms was characterized using two techniques, first by fan pressurization measurements of the envelope airtightness and later by tracer gas measurements of the air change rate assuming different envelope conditions. A total of 110 tracer gas measurements were made and the results validated ventilation protocols that were tested afterward. The results of the ventilation protocol implementation were encouraging and, overall, a decrease on the CO2 concentration was observed without modifying the comfort conditions. Nevertheless, additional measurements must be performed for winter conditions.

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DHEC’s Bureau of Air Quality issues construction and operating permits. Here’s a brief overview of the air permitting public notice process, including timeframes for public notice comment periods and information on which permits are required by law to include public notices.

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The intent of this booklet is to provide a basic overview of the process to determine if equipment is eligible for a construction permit exemption. This guide will help you determine if a permit is needed or if your equipment is exempt.

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Quality management provides to companies a framework to improve quality in overall systems, reduction of costs, reallocation of resources efficiently, correct planning of strategies, prevent or correct errors in the right time and increase the performance of companies. In this text, we discuss the different theories in this field, their obligatory or non-obligatory compliance, the importance of quality management for exporting companies and a case study of a Colombian firm that its main objective is to manage quality. In conclusion, we find out that there is different types of quality management systems such as Juran’s trilogy, Deming 14 points, Six sigma, HACCP, and so on; also that companies have to manage suppliers and that quality has a positive influence on exports volume; in the case of Colombian small and medium enterprises, it can be mentioned that the majority has implemented tools regarding quality management but is not enough.

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The purpose of this chapter is to enable registered health and social care prac - titioners to assume a clinical and/or a professional leadership role in quality management in the health and social care sectors. The contents in this chap - ter will strengthen the management competences of practitioners working in these sectors, including critical thinking, critical reflection, problem solving and decision -making, thus improving the quality in health and social care services.

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The relationship between the themes of Total Quality Management (TQM) and Social Responsibility (CSR) through the concepts, approaches and models of excellence is a reality of sustainable and stable companies. Being organizations, people, act correctly and rightly do in society go through a quality management and social responsibility thereof. It is based on these two philosophies (Total Quality Management and Corporate Social Responsibility), which developed this literature review work, essentially based on a relational analysis in two papers, namely: "TQM and CSR Nexus" by Ghobadian et al. (2007) and "The Corporate Social Responsibility Audit Within the Quality Management Framework," de Kok et al. (2001) and applied to an organizational situation in concrete: the Nabeiro Delta Cafés Group - SGPS, SA.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.