published_or_final_version / Chemistry / Master / Master of Philosophy

CNEN / Tendo em vista o crescente interesse dos organismos internacionais e nacionais em se conhecer os níveis de radônio no ar, em águas, principalmente em poços, e a escassez destes dados em esfera nacional, o grupo de pesquisa em radiações da UTFPR, em colaboração com o Centro de Desenvolvimento da Tecnologia Nuclear (CDTN / CNEN) e com o Instituto de Radioproteção e Dosimetria (IRD / CNEN) tem mantido uma parceria onde se realizam medidas de radônio no ar, solos e águas. Estas medidas têm sido feitas pelo grupo desde 2003 e o laboratório especializou-se em medidas no ar, por meio de detectores do estado sólido e em solo e água, por meio de equipamento eletrônico de medidas instantâneas. O objetivo desta tese é avaliar a os níveis de concentração de radônio 222Rn em residências e postos de trabalho (indoor) no estado do Paraná, mais especificamente na região metropolitana de Curitiba e verificar os níveis de concentração de 222Rn em águas de poços desta região. O trabalho apresenta os resultados das concentrações de 222Rn em ambientes residenciais, postos de trabalho e em águas de poços da região. As medidas indoor foram feitas por meio de detectores do estado sólido CR-39. A densidade de traços por cm2 para cada detector foi determinada. Os cálculos das concentrações de 222Rn nos ambientes foram feitos a partir de metodologia de calibração do sistema detector, desenvolvida especificamente para estas medidas. O trabalho de calibração foi desenvolvido em conjunto com o CDTN a partir de irradiações feitas no National Institute of Radiological Sciences (NIRS). As concentrações de 222Rn nas residências ficaram, na sua maioria, abaixo de 100 Bq/m3, com apenas um caso onde a concentração ficou entre 200 e 400 Bq/m3. Com relação aos postos de trabalho, todas as medidas de concentração de 222Rn ficaram abaixo de 100 Bq/m3. As concentrações de 222 Rn nas amostras das águas de poços foram medidas, em intervalos de cerca de quatro dias, por meio do monitor de radônio AlphaGUARD PQ2000 PRO. Os cálculos das concentrações de atividade iniciais de radônio na água foram feitos a partir da curva de decaimento do 222Rn e do equilíbrio secular entre o 222Rn e o 226Ra, observados depois de 30 dias. Os resultados indicaram que cerca de 70% dos valores das concentrações de 222Rn ficaram acima do valor recomendado pela USEPA, de 11,1 Bq/L, representando risco radiológico causado por este radionuclídeo. / Considering the growing interest of International Agencies and national Governmental organs in studies and measurements of radon activity in air, soil gas and ground water (mainly from artesian wells) as well as scarceness of such measurements at Brazilian territory, present studies were initiated by the Laboratory of Applied Nuclear Physics of Federal University of Technology – Paraná (UTFPR) in collaboration with the Institute of Radiation Protection and Dosimetry (IRD) and the Center of Nuclear Technology Development (CDTN) of Brazilian Commission on Nuclear Energy (CNEN). This Collaboration started in 2003. Radon monitoring program is based mainly on use of Solid State Nuclear Track Detectors for radon activity measurements in air. Continuous electronic radon detectors are used for radon measurements in soil gas and water. Current work presents the results of indoor 222Rn activity of dwellings and working places of Curitiba-PR and radon concentration in ground water samples from artesian wells from aquifers of the same area. The indoor measurements of radon activity were performed using Solid State Nuclear Track Detectors CR-39. After the exposition, CR-39 detectors were submitted to chemical development which permitted to make alpha particle tracks counting. The results of calibration of CR-39 together with efficiency of used exhalation chambers as well as alpha particle tracks chemical development procedure were erformed in cooperation with CDTN and collaboration with the National Institute of Radiological Sciences (NIRS). The major part of indoor 222Rn concentration in residences was found below 100 Bq/m3. In the case of working places, all measurements present 222Rn concentration bellow 100 Bq/m3. The studies of radon activity in water were performed using the samples of water from artesian wells submitted to recursive measurements by instant radon detector AlphaGUARD PQ2000 PRO during few weeks with intervals of about 4 days between each measurement approximately. The calculations of initial radon activity in water were done considering the 222Rn decay correction as well as equilibrium level of 222Rn and 226Ra observed after 30 days of measurements. Obtained results show that about 70% measured activity levels of 222Rn are higher than recommended value of 11.1 Bq/L which represent the risk for the human health associated with this radionuclide.

by Shu Keung Choi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 145-150). / ABSTRACT --- p.i / ACKNOWLEDGMENTS --- p.iii / TABLE OF CONTENTS --- p.iv / LIST OF FIGURES --- p.ix / LIST OF PLATES --- p.xi / LIST OF TABLES --- p.xii / Chapter CHAPTER 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Concerns on Current Air Quality Modeling Process --- p.2 / Chapter 1.2 --- Objective --- p.2 / Chapter 1.3 --- Rationale --- p.4 / Chapter 1.4 --- System Overview --- p.4 / Chapter 1.5 --- Questions --- p.6 / Chapter 1.6 --- Thesis Organization --- p.6 / Chapter CHAPTER 2. --- LITERATURE REVIEW --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Geographic Information System --- p.8 / Chapter 2.2.1 --- Data Assimilation --- p.9 / Chapter 2.2.1.1 --- Data Representation --- p.9 / Chapter 2.2.1.2 --- Data Format --- p.10 / Chapter 2.2.1.3 --- Data Alignment --- p.11 / Chapter 2.2.2 --- Modeling Support --- p.11 / Chapter 2.3 --- Environmental Modeling --- p.12 / Chapter 2.4 --- Integration of GIS and Environmental Modeling --- p.15 / Chapter 2.4.1 --- The Need for Integration --- p.15 / Chapter 2.4.2 --- Forms of Integration --- p.17 / Chapter 2.5 --- Air Quality Modeling --- p.20 / Chapter 2.5.1 --- Classes of Models --- p.21 / Chapter 2.5.1.1 --- Classification by Spatial Scale --- p.21 / Chapter 2.5.1.2 --- Classification by Modeling Approach --- p.22 / Chapter 2.6 --- Gaussian Plume Models --- p.24 / Chapter 2.6.1 --- Formulation --- p.24 / Chapter 2.6.2 --- Determination of σy and σz --- p.25 / Chapter 2.6.3 --- The Stability Classification --- p.26 / Chapter 2.6.4 --- Estimation of σy and σz --- p.27 / Chapter 2.6.5 --- Assumptions in the Gaussian Model --- p.30 / Chapter 2.7 --- Air Quality Model Evaluation --- p.31 / Chapter 2.7.1 --- Model Uncertainties --- p.31 / Chapter 2.7.1.1 --- Inherent Uncertainty --- p.31 / Chapter 2.7.1.2 --- Reducible Uncertainty Errors --- p.33 / Chapter 2.7.1.2.1 --- Meteorological Data Errors --- p.33 / Chapter 2.7.1.2.2 --- Emission Data Errors --- p.34 / Chapter 2.7.1.2.3 --- Model Errors --- p.34 / Chapter 2.7.2 --- Operational Performance Evaluation --- p.36 / Chapter 2.7.2.1 --- Woods Hole Performance Measures --- p.36 / Chapter 2.7.2.2 --- Fractional Bias and Fractional Scatter --- p.38 / Chapter 2.7.2.3 --- Measuring the Normalized Ratios --- p.39 / Chapter 2.7.2.4 --- Combination of Statistical Measures --- p.40 / Chapter 2.8 --- Visualization --- p.43 / Chapter 2.8.1 --- Visualization Software Framework --- p.43 / Chapter 2.8.2 --- GIS and Visualization --- p.46 / Chapter 2.9 --- Conclusion --- p.47 / Chapter CHAPTER 3. --- SYSTEM DESIGN --- p.48 / Chapter 3.1 --- System Overview --- p.48 / Chapter 3.2 --- Supported Models --- p.50 / Chapter 3.3 --- System Software Platforms --- p.51 / Chapter 3.3.1 --- ARC/INFO --- p.52 / Chapter 3.3.1.1 --- Overview --- p.52 / Chapter 3.3.1.2 --- The Role in the System --- p.53 / Chapter 3.3.2 --- Advanced Visualization System (AVS) --- p.54 / Chapter 3.3.2.1 --- Overview --- p.54 / Chapter 3.3.2.2 --- The Role in the System --- p.54 / Chapter 3.4 --- System Requirements and Specification --- p.56 / Chapter 3.4.1 --- Notation --- p.56 / Chapter 3.4.2 --- Data Preprocessing --- p.57 / Chapter 3.4.3 --- Data Postprocessing --- p.63 / Chapter 3.4.4 --- Model Performance Evaluation --- p.68 / Chapter 3.4.5 --- Visualization --- p.74 / Chapter 3.4.5.1 --- Reading ARC/INFO Data --- p.74 / Chapter 3.4.5.2 --- Applying Visualization Techniques --- p.77 / Chapter 3.4.5.2.1 --- Surface Mesh --- p.77 / Chapter 3.4.5.2.2 --- Multi-window Approach --- p.79 / Chapter 3.5 --- Data File Format --- p.85 / Chapter CHAPTER 4. --- A TEST CASE --- p.92 / Chapter 4.1 --- Introduction --- p.92 / Chapter 4.2 --- Test Case Components --- p.92 / Chapter 4.2.1 --- Study Area --- p.92 / Chapter 4.2.2 --- Source Data --- p.93 / Chapter 4.2.3 --- Air Quality Model - MPTER --- p.93 / Chapter 4.2.4 --- Meteorological Data Preprocessor - RAMMET --- p.95 / Chapter 4.3 --- Executing the Test Case --- p.95 / Chapter 4.3.1 --- Main Menu --- p.95 / Chapter 4.3.2 --- Viewing the study area --- p.96 / Chapter 4.3.3 --- Data Preprocessing --- p.96 / Chapter 4.3.3.1 --- Define Data Mapper --- p.98 / Chapter 4.3.3.2 --- Execute Data Preprocessor --- p.101 / Chapter 4.3.3.3 --- Meteorological Data Preprocessing --- p.102 / Chapter 4.3.3.4 --- Model Input File Editing --- p.103 / Chapter 4.3.3.5 --- Discussions --- p.105 / Chapter 4.3.4 --- Model Execution --- p.107 / Chapter 4.3.5 --- Data Postprocessing --- p.107 / Chapter 4.3.5.1 --- Import Model Result to GIS --- p.108 / Chapter 4.3.5.2 --- Iso-line of Concentration Map --- p.108 / Chapter 4.3.5.3 --- Discussions --- p.109 / Chapter 4.3.6 --- Model Performance Evaluation --- p.112 / Chapter 4.3.6.1 --- Program Execution --- p.113 / Chapter 4.3.6.2 --- Discussions --- p.113 / Chapter 4.3.7 --- Visualization --- p.116 / Chapter 4.3.7.1 --- Surface Mesh --- p.116 / Chapter 4.3.7.2 --- Multi-window Approach for 4D Data set --- p.117 / Chapter 4.3.7.2.1 --- Overview --- p.117 / Chapter 4.3.7.2.2 --- Overall Controls and Relations between Viewers --- p.121 / Chapter 4.3.7.2.3 --- Independent Controls within Each Viewers --- p.122 / Chapter 4.3.7.2.4 --- "The x,y,z-volume Viewer" --- p.123 / Chapter 4.3.7.2.5 --- "x,y,t-volume in ViewerZ" --- p.128 / Chapter 4.3.7.2.6 --- Other Viewers --- p.132 / Chapter 4.3.7.3 --- Discussions --- p.134 / Chapter 4.4 --- Conclusion --- p.137 / Chapter CHAPTER 5. --- CONCLUSION --- p.138 / Chapter 5.1 --- System Design Summary --- p.138 / Chapter 5.2 --- Summary of the Functions --- p.139 / Chapter 5.2.1 --- Data Preprocessing --- p.139 / Chapter 5.2.2 --- Data Postprocessing --- p.140 / Chapter 5.2.3 --- Model Evaluation --- p.140 / Chapter 5.2.4 --- Visualization --- p.141 / Chapter 5.3 --- Further Research --- p.143 / BIBLIOGRAPHY --- p.145

Orientador: Edson Tomaz / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-10T00:00:54Z (GMT). No. of bitstreams: 1 Albuquerque_EdlerLinsde_D.pdf: 18576988 bytes, checksum: f5a08b5bbd306ca352ba5e96455e69d8 (MD5) Previous issue date: 2007 / Resumo: Realizou-se um estudo experimental dos Compostos Orgânicos Voláteis (COV) encontrados na atmosfera urbana da Região Metropolitana de São Paulo (RMSP). O objetivo principal foi medir as concentrações de COV, procurando identificar, por meio de análises multivariadas, relações entre estas concentrações, parâmetros meteorológicos e concentrações de outros poluentes. Métodos de amostragem passiva e ativa foram empregados utilizando tubos de aço contendo o sólido adsorvente TENAX TA. A quantificação das amostras ocorreu por dessorção térmica automática e cromatografia gasosa com detecção por ionização em chama. Analisou-se COV selecionados, incluindo alcanos, cicloalcanos e compostos aromáticos. Diversos aspectos foram investigados em estudos específicos: emissão veicular, variabilidade diária das concentrações, emprego da amostragem passiva, potencial para formar ozônio etc. As concentrações registradas em cada campanha variaram bastante em função de aspectos associados a características locais das fontes de emissão, horários de coleta, fatores sazonais e meteorológicos. Verificou-se que tolueno, m,p-xilenos, n-hexano, etilbenzeno e 1,2,4-trimetilbenzeno foram os COV encontrados em maiores concentrações na maioria dos estudos realizados, estando os mesmos entre os mais emitidos pelos veículos e entre aqueles com maior potencial para formar ozônio. No local monitorado, o perfil de variação temporal das concentrações de COV foi diferente em função de condições sazonais e/ou meteorológicas. A validação da amostragem passiva possibilitou estimar taxas de amostragem dos COV, as primeiras da literatura científica para vários compostos e as primeiras obtidas numa atmosfera urbana de cidades brasileiras. Isto viabilizou a realização de um monitoramento passivo simultâneo em oito locais diferentes, permitindo verificar as vantagens deste tipo de coleta. Acredita-se que os resultados desta pesquisa possam auxiliar na criação de planos de monitoramento para os COV / Abstract: The aim of this research was an experimental study of Volatile Organic Compounds (VOCs) found in the urban atmosphere of Metropolitan Area of São Paulo (MASP). The main purpose was to measure atmospheric concentrations of VOCs. Multivariate analyses were used to identify relationships among VOCs concentration, meteorological parameters and concentrations of other pollutants. Passive and active sampling methods were applied. Steel tubes packed with adsorbent TENAX TA were employed. The samples were quantified by automatic thermal desorption and gas chromatography with flame ionization detection. Selected VOCs were analyzed, including alkanes, cycloalkanes and aromatic compounds. Many topics related to VOCs were investigated: vehicular emissions, time variation of concentrations, employ of passive sampling, potential of ozone formation etc. For this, some specific studies were conducted. VOCs concentration vary a lot in each campaign in function of aspects associated to local characteristics of emission sources, sampling time, season and meteorological factors. In most of performed studies toluene, m,p-xylenes, n-hexane, ethylbenzene and 1,2,4-trimethylbenzene were VOCs found in higher concentrations. Additionally, such compounds were also found among VOCs with higher vehicular emission factors and higher ozone forming potentials. At the monitoring site, VOCs concentrations have shown distinct profile of time variation for different seasonal and meteorological conditions. VOCs uptake rates were estimated from the validation of passive sampling process. These uptake rates were the first found for many VOCs and the first found in an urban atmosphere of Brazilian cities. This fact became possible to perform a simultaneous passive monitorization campaign in eight different sites at MASP, verifying the advantages of this type of sampling strategy. It is believed that the results of this research may aid in the creation of monitoring programs for VOCs / Doutorado / Desenvolvimento de Processos Químicos / Mestre em Engenharia Química