Today people spend all the more time indoors. Asthma, allergies and Sick Building Syndrome (SBS) are affecting an increasing number of people. The remedy for all these affections has long been to increase the volume flow of outdoor air in the ventilation but at the same time cities all over the world are struggling with air pollution and smog rising above endangering levels. Living filters present a new solution where part of the indoor air can be purified and recirculated in a building. This project has compiled research on the area to describe the how and why concerning air purification by plants. Independent research conclude that plants can reduce most hazardous chemical agents in the air. Climate change, global warming and increasing demands on energy performance induces a race for countries and companies to improve energy efficiency in all sectors. To the building engineering sector living filters presents a unique solution to cut ventilation energy loses. A powerful simulation tool IDA ICE was used to estimate the energy saving capacity when a living filter is applied in the lunch room of an office floor. Another simulation software; Comsol Multiphysics was used to illustrate the aspects of ventilation flow when a living filter cabinet is deployed in a room. The simulation results show that for three living filter cabinets each measuring 0,7x0,8x1,73 cm the buildings energy usage is reduced with more than the living filters use to operate. The single room simulations then show how a living filter can be accommodated with both mixing and displacing ventilation. However, these simulations also illustrate the importance of the living filters placement to achieve maximum ventilation efficiency.  The conclusions from this work are that living filters can reduce building sector energy demands and provide significant indoor environmental benefits. The main issue for using living filters is identified to be building regulations putting strict demands on outdoor air flow and that the hygienic function of each living filter must be verified before it may replace outdoor air.

Air quality monitoring is one of several important tasks carried out in the area of environmental science and engineering. Accordingly, the development of air quality predictive models can be very useful as such models can provide early warnings of pollution levels increasing to unsatisfactory levels. The literature review conducted within the research context of this thesis revealed that only a limited number of widely used machine learning algorithms have been employed for the modelling of the concentrations of atmospheric gases such as ozone, nitrogen oxides etc. Despite this observation the research and technology area of machine learning has recently advanced significantly with the introduction of ensemble learning techniques, convolutional and deep neural networks etc. Given these observations the research presented in this thesis aims to investigate the effective use of ensemble learning algorithms with optimised algorithmic settings and the appropriate choice of base layer algorithms to create effective and efficient models for the prediction and forecasting of specifically, ground level ozone (O3). Three main research contributions have been made by this thesis in the application area of modelling O3 concentrations. As the first contribution, the performance of several ensemble learning (Homogeneous and Heterogonous) algorithms were investigated and compared with all popular and widely used single base learning algorithms. The results have showed impressive prediction performance improvement obtainable by using meta learning (Bagging, Stacking, and Voting) algorithms. The performances of the three investigated meta learning algorithms were similar in nature giving an average 0.91 correlation coefficient, in prediction accuracy. Thus as a second contribution, the effective use of feature selection and parameter based optimisation was carried out in conjunction with the application of Multilayer Perceptron, Support Vector Machines, Random Forest and Bagging based learning techniques providing significant improvements in prediction accuracy. The third contribution of research presented in this thesis includes the univariate and multivariate forecasting of ozone concentrations based of optimised Ensemble Learning algorithms. The results reported supersedes the accuracy levels reported in forecasting Ozone concentration variations based on widely used, single base learning algorithms. In summary the research conducted within this thesis bridges an existing research gap in big data analytics related to environment pollution modelling, prediction and forecasting where present research is largely limited to using standard learning algorithms such as Artificial Neural Networks and Support Vector Machines often available within popular commercial software packages.

Air pollution is becoming an increasing problem in Sub-Saharan Africa. Every year, it claims the lives of more than 712,000 people, which is more than the number of lives claimed by unsafe water and malnutrition. However, there is a lack of data on the topic in this region. I therefore designed my study to contribute to the small but growing literature on air pollution in Sub-Saharan Africa. My study looks at the relationship between local seasonal variations and air pollution levels. I am focusing on fine particles (PM2.5) because of their impacts on public health. My study revealed that average air pollution levels in Gabon meet the World Health Organization standards (WHO). However, daily variations suggest PM2.5 levels that exceed the recommended levels, which can be harmful to human health. I therefore recommend addressing pollution sources as a way of reducing overall pollution levels in the country.

As perspectivas de expansão da produção de energia transformam a região de Candiota em um cenário propício para o estudo da poluição atmosférica. A importância deste assunto tornou-se evidente com o aumento das emissões de poluentes causado pelo crescimento das áreas urbana e industrial. Com a ampliação do Complexo Termelétrico, construção de Candiota III, e, principalmente, por estar previsto a instalação de novas indústrias nesta região, este estudo tem como foco principal avaliar o impacto deste crescimento industrial na qualidade do ar. A metodologia para o desenvolvimento deste trabalho dispõe como principal ferramenta um modelo matemático de dispersão, AERMOD, representando analiticamente o comportamento do poluente, dióxido de enxofre, durante o processo de dispersão no ar, levando em conta as características das fontes de emissão, da topografia da área de estudo e das condições meteorológicas de dispersão. Através da modelagem numérica, foram comparados os dados de concentrações preditos pelo modelo com os dados observados provenientes de estações meteorológicas localizadas no entorno da Usina Termelétrica Presidente Médice, para campanhas anteriores e posteriores à operação de Candiota III. A análise dos resultados foi feita com auxílio de índices estatísticos recomendados na literatura científica para a avaliação de modelos de qualidade do ar. A utilização do modelo AERMOD para uma avaliação preliminar do impacto causado pela operação de Candiota III mostrou-se eficiente. Levando-se em consideração todas as restrições incorporadas aos modelos gaussianos, o modelo apresentou uma tendência de subestimar os valores observados. A utilização de novas tecnologias indicou que ocorrera um aumento da eficiência nos processos de combustão bem como de dessulfurização em virtude de se constatar, através dos resultados obtidos para as concentrações máximas diárias, uma diminuição na emissão de dióxido de enxofre para a atmosfera. Os resultados das concentrações máximas diárias de dióxido de enxofre para o cenário anterior a operação de Candiota III (2003) foram superiores aos simulados para o período posterior (2011). Com uma confiabilidade de 90 e 80%, respectivamente, para os cenários em que as concentrações máximas e médias 24hs foram simuladas e confrontadas com as observadas nos receptores, os resultados obtidos reforçam que as concentrações calculadas pelo modelo de dispersão, apresentam uma concordância satisfatória com os dados observados. / The perspectives for expansion of energy production transform the region of Candiota in a favorable scenario for the study of air pollution. The importance of this issue has become evident with the increase in pollutant emissions caused by the growth of urban and industrial areas. With the expansion of Thermoelectric Complex, construction of Candiota III, and especially for the up-coming establishment of new industries in this region, this study aims to evaluate the impact of industrial growth on air quality. The methodology for the development of this work has as main tool the dispersion of a mathematical model, AERMOD, analytically representing the behavior of the pollutant, sulfur dioxide, during the process air dispersion, taking into account the characteristics of the emission sources, the topography of the study area and meteorological dispersion conditions. Through numerical modeling, it was compared the data of the concentrations predicted by the model with the observed data from meteorological stations located around the Thermoelectric Power Plant “Presidente Médice” for this experimental campaigns before and after the operation Candiota III. The analysis of the results was performed with the aid of statistical indexes recommended in the scientific literature for evaluation of models of air quality. The use of the AERMOD for a preliminary assessment of the impact caused by the operation of Candiota III was efficient. Taking into account all the restrictions of the Gaussian models, the model tended to underestimate the observed values. The use of new technologies indicated that there was an increase in the efficiency of combustion processes and desulfurization due to the results obtained for the maximum daily concentrations, a decrease in the emission of sulfur dioxide into the atmosphere. The results of the maximum daily concentrations of sulfur dioxide to the scenario presented before the operation of Candiota III (2003) were higher than the period after simulated (2011). With a reliability of 90% and 80%, respectively, for scenarios where the peak concentrations and averages 24 hours were simulated and compared with those observed in receptors, the results obtained reinforce that the concentrations calculated by the dispersion model, present a satisfactory agreement with the observed data.

Made available in DSpace on 2014-06-11T19:27:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-08-18Bitstream added on 2014-06-13T20:16:31Z : No. of bitstreams: 1 corbi_kp_me_arafcf.pdf: 422770 bytes, checksum: 6a87a5e20c6db8ffd363817b89326bde (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Universidade Estadual Paulista (UNESP) / Os principais parâmetros de qualidade do ar de um ambiente naturalmente ventilado e outro climatizado, destinados a ocupação comum, foram analisados. As variáveis ambientais consideradas foram concentração de bactéria (UFC/m3 de ar), concentração de fungo (UFC/m3 de ar), taxa de CO2 (ppm), umidade relativa do ar (%), velocidade (Km/h), temperatura (ºC) e concentração de partículas (æg/m3 de ar). Nossos achados apontam que os parâmetros mais influenciados pela ocupação dos ambientes são taxa de CO2 e concentração de aerossóis bacterianos, porém os valores médios no ambiente ventilado foram menores que no climatizado. Em decorrência da utilização, cada vez mais freqüente, de sistemas de condicionamento do ar, esse trabalho visou colaborar com o conhecimento dos principais parâmetros de qualidade de ar em ambientes climatizados e naturalmente ventilados. Para que a boa qualidade do ar de interiores possa ser mantida, em ambientes onde a ventilação é constante, é imprescindível o controle do número de ocupantes. / The mainly environmentals parameters of the air quality in ventilatized and climatized ambients, destinated to the common occupation, were analyzed in this research. The evaluated environmental variables were the concentration of bacteria (CFU/m3 of air), concentration of fungo (CFU/m3 of air), rate of carbon dioxide (ppm), relative air humidity (%), speed (Km/h), temperature (ºC) and concentration of particles (æg/m3 of air). The correlation among the number of people, and the other variables, obtain significance, in the two samples, for the concentration of bacterial aerosols, CO2 rate and the temperature for the climatized ambient. In the ventilated ambient only the CO2 concentration and the number of people was correlated in the two samples.

Thesis (MTech (Chemical Engineering))--Cape Peninsula University of Technology, 2006 / Measurement and forecasting of visibility is essential in assessing the extent of visibility degradation (haze) due to air pollution in Cape Town. Rapid impairment in visibility over the years forced the City ofCape Town to initiate the Brown Haze I (BH I) study in September 1997. The main objective of the Brown Haze I Study was to determine the contribution of all major pollutant sources to the brown haze, and to determine other factors that contribute to haze formation. However to date no study has attempted to devise quantitative methods to monitor visibility in Cape Town. This study reports on a new method of measuting visibility using Digital Image Processing. An hourly series of time-stamped images of three scenic vistas was recorded over a period of 8 months (20060318 to 20061031) using three co-located Sanyo E-6311xP-H digital cameras equipped with E-50500D 20 to lOOrnrn Variable-focal Auto Iris Lenses. The cameras were orientated in three directions (approximately due west, north and east). These time- stamped images were archived for subsequent digital image processing. The average image intensities of selected areas of each image were calculated using the histogram function of digital image processing software (PhotoshopTM 7.0), to obtain the inherent and apparent contrast ratios. The inherent and apparent contrast measurements were then used to calculate light extinction coefficient (bex') and the visual range (VR).

As perspectivas de expansão da produção de energia transformam a região de Candiota em um cenário propício para o estudo da poluição atmosférica. A importância deste assunto tornou-se evidente com o aumento das emissões de poluentes causado pelo crescimento das áreas urbana e industrial. Com a ampliação do Complexo Termelétrico, construção de Candiota III, e, principalmente, por estar previsto a instalação de novas indústrias nesta região, este estudo tem como foco principal avaliar o impacto deste crescimento industrial na qualidade do ar. A metodologia para o desenvolvimento deste trabalho dispõe como principal ferramenta um modelo matemático de dispersão, AERMOD, representando analiticamente o comportamento do poluente, dióxido de enxofre, durante o processo de dispersão no ar, levando em conta as características das fontes de emissão, da topografia da área de estudo e das condições meteorológicas de dispersão. Através da modelagem numérica, foram comparados os dados de concentrações preditos pelo modelo com os dados observados provenientes de estações meteorológicas localizadas no entorno da Usina Termelétrica Presidente Médice, para campanhas anteriores e posteriores à operação de Candiota III. A análise dos resultados foi feita com auxílio de índices estatísticos recomendados na literatura científica para a avaliação de modelos de qualidade do ar. A utilização do modelo AERMOD para uma avaliação preliminar do impacto causado pela operação de Candiota III mostrou-se eficiente. Levando-se em consideração todas as restrições incorporadas aos modelos gaussianos, o modelo apresentou uma tendência de subestimar os valores observados. A utilização de novas tecnologias indicou que ocorrera um aumento da eficiência nos processos de combustão bem como de dessulfurização em virtude de se constatar, através dos resultados obtidos para as concentrações máximas diárias, uma diminuição na emissão de dióxido de enxofre para a atmosfera. Os resultados das concentrações máximas diárias de dióxido de enxofre para o cenário anterior a operação de Candiota III (2003) foram superiores aos simulados para o período posterior (2011). Com uma confiabilidade de 90 e 80%, respectivamente, para os cenários em que as concentrações máximas e médias 24hs foram simuladas e confrontadas com as observadas nos receptores, os resultados obtidos reforçam que as concentrações calculadas pelo modelo de dispersão, apresentam uma concordância satisfatória com os dados observados. / The perspectives for expansion of energy production transform the region of Candiota in a favorable scenario for the study of air pollution. The importance of this issue has become evident with the increase in pollutant emissions caused by the growth of urban and industrial areas. With the expansion of Thermoelectric Complex, construction of Candiota III, and especially for the up-coming establishment of new industries in this region, this study aims to evaluate the impact of industrial growth on air quality. The methodology for the development of this work has as main tool the dispersion of a mathematical model, AERMOD, analytically representing the behavior of the pollutant, sulfur dioxide, during the process air dispersion, taking into account the characteristics of the emission sources, the topography of the study area and meteorological dispersion conditions. Through numerical modeling, it was compared the data of the concentrations predicted by the model with the observed data from meteorological stations located around the Thermoelectric Power Plant “Presidente Médice” for this experimental campaigns before and after the operation Candiota III. The analysis of the results was performed with the aid of statistical indexes recommended in the scientific literature for evaluation of models of air quality. The use of the AERMOD for a preliminary assessment of the impact caused by the operation of Candiota III was efficient. Taking into account all the restrictions of the Gaussian models, the model tended to underestimate the observed values. The use of new technologies indicated that there was an increase in the efficiency of combustion processes and desulfurization due to the results obtained for the maximum daily concentrations, a decrease in the emission of sulfur dioxide into the atmosphere. The results of the maximum daily concentrations of sulfur dioxide to the scenario presented before the operation of Candiota III (2003) were higher than the period after simulated (2011). With a reliability of 90% and 80%, respectively, for scenarios where the peak concentrations and averages 24 hours were simulated and compared with those observed in receptors, the results obtained reinforce that the concentrations calculated by the dispersion model, present a satisfactory agreement with the observed data.

As perspectivas de expansão da produção de energia transformam a região de Candiota em um cenário propício para o estudo da poluição atmosférica. A importância deste assunto tornou-se evidente com o aumento das emissões de poluentes causado pelo crescimento das áreas urbana e industrial. Com a ampliação do Complexo Termelétrico, construção de Candiota III, e, principalmente, por estar previsto a instalação de novas indústrias nesta região, este estudo tem como foco principal avaliar o impacto deste crescimento industrial na qualidade do ar. A metodologia para o desenvolvimento deste trabalho dispõe como principal ferramenta um modelo matemático de dispersão, AERMOD, representando analiticamente o comportamento do poluente, dióxido de enxofre, durante o processo de dispersão no ar, levando em conta as características das fontes de emissão, da topografia da área de estudo e das condições meteorológicas de dispersão. Através da modelagem numérica, foram comparados os dados de concentrações preditos pelo modelo com os dados observados provenientes de estações meteorológicas localizadas no entorno da Usina Termelétrica Presidente Médice, para campanhas anteriores e posteriores à operação de Candiota III. A análise dos resultados foi feita com auxílio de índices estatísticos recomendados na literatura científica para a avaliação de modelos de qualidade do ar. A utilização do modelo AERMOD para uma avaliação preliminar do impacto causado pela operação de Candiota III mostrou-se eficiente. Levando-se em consideração todas as restrições incorporadas aos modelos gaussianos, o modelo apresentou uma tendência de subestimar os valores observados. A utilização de novas tecnologias indicou que ocorrera um aumento da eficiência nos processos de combustão bem como de dessulfurização em virtude de se constatar, através dos resultados obtidos para as concentrações máximas diárias, uma diminuição na emissão de dióxido de enxofre para a atmosfera. Os resultados das concentrações máximas diárias de dióxido de enxofre para o cenário anterior a operação de Candiota III (2003) foram superiores aos simulados para o período posterior (2011). Com uma confiabilidade de 90 e 80%, respectivamente, para os cenários em que as concentrações máximas e médias 24hs foram simuladas e confrontadas com as observadas nos receptores, os resultados obtidos reforçam que as concentrações calculadas pelo modelo de dispersão, apresentam uma concordância satisfatória com os dados observados. / The perspectives for expansion of energy production transform the region of Candiota in a favorable scenario for the study of air pollution. The importance of this issue has become evident with the increase in pollutant emissions caused by the growth of urban and industrial areas. With the expansion of Thermoelectric Complex, construction of Candiota III, and especially for the up-coming establishment of new industries in this region, this study aims to evaluate the impact of industrial growth on air quality. The methodology for the development of this work has as main tool the dispersion of a mathematical model, AERMOD, analytically representing the behavior of the pollutant, sulfur dioxide, during the process air dispersion, taking into account the characteristics of the emission sources, the topography of the study area and meteorological dispersion conditions. Through numerical modeling, it was compared the data of the concentrations predicted by the model with the observed data from meteorological stations located around the Thermoelectric Power Plant “Presidente Médice” for this experimental campaigns before and after the operation Candiota III. The analysis of the results was performed with the aid of statistical indexes recommended in the scientific literature for evaluation of models of air quality. The use of the AERMOD for a preliminary assessment of the impact caused by the operation of Candiota III was efficient. Taking into account all the restrictions of the Gaussian models, the model tended to underestimate the observed values. The use of new technologies indicated that there was an increase in the efficiency of combustion processes and desulfurization due to the results obtained for the maximum daily concentrations, a decrease in the emission of sulfur dioxide into the atmosphere. The results of the maximum daily concentrations of sulfur dioxide to the scenario presented before the operation of Candiota III (2003) were higher than the period after simulated (2011). With a reliability of 90% and 80%, respectively, for scenarios where the peak concentrations and averages 24 hours were simulated and compared with those observed in receptors, the results obtained reinforce that the concentrations calculated by the dispersion model, present a satisfactory agreement with the observed data.

O presente trabalho avaliou a qualidade do ar de uma área central da cidade de São Carlos-SP, mais precisamente no campus 1 da Universidade de São Paulo. Nessa região há grande movimentação de pessoas e veículos, principalmente durante o horário comercial. Esta avaliação foi feita com base na determinação de um dos parâmetros utilizados para verificar a qualidade do ar, o material particulado (MP) inalável em suspensão, ou seja, partículas que possuem diâmetro aerodinâmico menor ou igual a 10 μm e podem penetrar no sistema respiratório, sendo portanto, nocivas à saúde humana. O MP foi determinado em suas frações de 2,5 e 10 μm de diâmetro (MP10 e MP2,5). Duas metodologias diferentes foram utilizadas para determinar a concentração do material particulado em suspensão, fotometria por espalhamento de luz, através do equipamento ADR-1500 e gravimetria, através do PEM (Personal Enviromental Monitor). Os valores obtidos pelo método gravimétrico foram superiores aos resultados encontrados através da fotometria. As concentrações obtidas foram comparadas com os limites recomendados pela Organização Mundial da Saúde para o MP em suas frações de 2,5 e 10 μm, iguais respectivamente a 25 e 50 μg/m3. Além do material particulado foram obtidos dados para temperatura, umidade relativa e precipitação. As médias obtidas para as concentrações de MP10 e MP2,5, com o método gravimétrico, o qual fornece os resultados mais confiáveis, foram iguais respectivamente a 48,8 e 23,1 μg/m3, muito próximas portanto, de seus limites correspondentes. As menores concentrações obtidas para o MP10 foram, em sua maioria, verificadas em dias chuvosos, tanto através do PEM como do ADR. As concentrações de MP2,5, obtidas somente através do PEM, também apresentaram os menores valores em dias com chuva. Foi desenvolvido um modelo matemático que prevê o comportamento do MP10 durante as precipitações, evento este que se mostrou o mais importante na influência da concentração de material particulado atmosférico. / This study evaluated the air quality of a central area of the city São Carlos-SP, more precisely on the Campus 1 of the University of São Paulo. In this region there is a large movement of people and vehicles, manly during business hours. This evaluation was made based on determination of one parameter used to verify air quality, the inhalable particulate material (PM) suspended in the air, in other words, particles which have aerodynamic diameter less or equal to 10 μm and can penetrate in the respiratory system, therefore, harmful to human health. The PM was determined in its fractions from 2,5 and 10 μm of diameter (PM10 e PM2,5).). Two different methodologies were used to determinate the concentration of particulate suspended material, photometry by scattered light, using the equipment ADR-1500, and gravimetry, thru PEM (Personal Environmental Monitor). The data obtained from gravimetry were higher than the results found thru photometry. The concentrations found were compared to the limits recommended by World Health Organization for PM and its fractions of 2,5 and 10 μm, equal to 25 and 50 μg/m3. Besides PM, temperature, relative humidity and precipitation were measured. The average values for the concentrations of PM10 and PM2,5 , using gravimetry, which provide more reliable results, it were equal to 48,8 and 23,1 μg/m3, therefore really close to their corresponding limits. The lower concentrations seen for PM10 were, mostly, verified on rainy days, using PEM and ADR. The concentrations of PM2,5 , obtained just using PEM, also had the lowest values during rainy days. A mathematical model was developed to predict PM10 behavior during precipitations, this event has shown to have the most important influence on the concentration of atmospheric particulate matter.

In order to understand the impact from a point source of pollution a comprehensive air quality monitoring programme must be in place. Measurement stations are at fixed locations and can only measure the relevant concentration if the wind is blowing in a particular direction. With changing wind direction, a measurement station needs to be coupled with a dispersion model to predict the impact from a point source, such as the BCL Limited smelter. The smelter produces 55 500 tonnes per annum of nickel/copper granules; in the process emitting waste gases to the atmosphere through a 153 m stack. The EEGAIR-BCL1. dispersion model was developed for BCL Limited to complement the air quality monitoring programme in the Selebi-Phikwe area. The model was developed for the smelter specifically, using local meteorological data at Selebi-Phikwe and smelter specific emission data. Results from the model were tested against data obtained from existing measurements stations at Selebi-Phikwe for May 2002, using statistical analyses. The average index of agreement indicates that the model predictions were more accurate for Kopano (0,44) and SPSS (0,25) stations than for WUC (0,08) station. Yearly averaged emission data was used for model input and better correlation can be expected when using actual hourly and/or monthly emission data. Based on the EEGAIR-BCl1 dispersion model results, it was found that the highest impact from the smelter stack was at a distance of 4 km to 7 km west from the stack. The model results indicate that, on average, the impact from the smelter stack in residential areas of Selebi-Phikwe was between 0 and 50 µ/m3 for May 2002. / Dissertation (MEng(Environmental Engineering))--University of Pretoria, 2006. / Chemical Engineering / unrestricted