Orientador: Silvia Regina Lucas de Souza / Resumo: Em ambientes de produção animal o processo de análise das condições de conforto térmico pode ser realizado mediante o cálculo de índices de conforto térmico e da elaboração de mapas de variabilidade espacial de parâmetros meteorológicos e dos próprios índices de conforto térmico. Os métodos atuais para análise do bem-estar animal, especificamente aqueles por meio de mapas de índices de conforto térmico, são realizados em programas de computador utilizando-se softwares específicos de interpolação de dados. Esses processos, por sua vez, não permitem que avaliações de conforto térmico sejam realizadas facilmente no próprio local de coleta de dados. Assim, esse trabalho foi realizado com o objetivo de desenvolver um sistema para criação de mapas de variabilidade espacial da temperatura do ar e de índices de conforto térmico de animais, utilizando o método interpolador IDW (Inverse Distance Weighted), ou Inverso da Distância Ponderada. O sistema desenvolvido é composto por um aplicativo Android e dispositivos de transmissão e recepção de dados meteorológicos. O aplicativo foi desenvolvido por meio da linguagem de programação orientada a objetos Java, mediante o ambiente de desenvolvimento integrado Android Studio. Já os dispositivos móveis foram criados utilizando-se sensores de baixo custo de temperatura do ar, temperatura de globo negro e umidade relativa, juntamente com microcontroladores de plataforma eletrônica de código aberto – Arduino. O algoritmo desenvolvido para o aplic... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In animal production environments, the process of analysis of thermal comfort conditions may be carried out through the calculation of the thermal comfort index and the creation of maps showing spatial variabilities of meteorological parameters and the thermal comfort indexes. The current methods for analysis of animal well fare, especially those including maps of thermal comfort indexes, are carried out using computer programs with specific software of data interpolation. On the other hand, these processes don’t allow the evaluations of thermal comfort to be easily performed in the data collection site. Therefore, the aim of this study was developing a system for creation of maps with spatial variability of the air temperature and thermal comfort of animals, using the IDW (Inverse Distance Weighted) interpolation method. The system created is formed by an Android app and devices of transmission and reception of meteorological data. The app was developed using the Java programming language, through the Android Studio integrated development environment. The mobile devices were made using low cost air temperature, black globe temperature and relative humidity sensors, and microcontrollers of open source electronic platform – Arduino. The algorithm developed for the Android app was validated by means of comparing the air temperature figures measured, and those interpolated by the app in a broiler shed. On the other hand, the transmission and reception of data were validated via ... (Complete abstract click electronic access below) / Doutor

Northeastern British Columbia (Canada) is a region of oil and gas exploitation. Oil and gas extraction activities can emit contaminants, including radon, but studies on indoor air contaminants in regions of oil and gas exploitation are scarce. This study aimed to evaluate the association between the density/proximity of oil and gas wells and indoor air radon concentrations in Northeastern British Columbia. Data from the British Columbia Radon Data Repository (BCRDR) and the Exposures in the Peace River Valley study (EXPERIVA) were used, with 497 radon measurements taken from dwellings between 1992 and 2019. Within different buffer zones around each dwelling (2.5, 5 and 10 km), well density was calculated and an exposure metric, Inverse Distance Weighting (IDW), of both well density and proximity was derived. Linear regression models were used to evaluate the associations between well density and IDW and indoor air radon concentrations while adjusting for the floor where measurement was taken. A higher radon concentration was measured in basements than upper floors. Statistically significant and negative associations (p<0.05) were observed between well density/proximity and radon concentrations. For example, an increase of one well within 10 km was associated with a modest decrease of 0.1% (95% CI: 0.05; 0.20) in radon concentrations. We observed no positive association between well density/proximity measurements and radon concentrations. The negative associations were primarily influenced by radon measurements made in 1992, when oil and gas development used very little hydraulic fracturing. Additional studies with more measurements, information on dwelling type, and phase of oil and gas operations could allow a more precise and powerful analysis. / L’exploitation gazière et pétrolière, parfois associée à de la fracturation hydraulique, peut entraîner l’émission de contaminants comme le radon dans les régions présentant des puits d’exploitation. L’objectif de cette étude était d’évaluer l’association entre la densité/proximité des puits de gaz et de pétrole et les concentrations de radon dans l’air intérieur des résidences du Nord-Est de la Colombie-Britannique. Une base de données comprenant 497 concentrations de radon mesurées dans des résidences de cette région a été utilisée. Cette base de données contenait plusieurs études de mesure du radon réalisées entre 1992 et 2019, dont des données de l’étude EXPERIVA et un regroupement de données (British Columbia Radon Data Repository) réalisé par le British Columbia Centre for Disease Control. En matière d’exposition, une approche par pondération de la distance inverse (appelée Inverse Distance Weighting, ou IDW), et le nombre des puits furent calculés dans trois périmètres autour des habitations (2.5, 5 et 10 km), permettant d’estimer pour chaque habitation l’importance de l’exposition aux puits d’exploitation (par leur proximité et la densité des puits). L’analyse de l’association entre les IDW ou le nombre de puits, et la concentration de radon a été faite par analyse de régression linéaire multiple, ajustée pour l’étage de la résidence auquel la mesure fut réalisée (sous-sol ou autre étage). Une plus grande concentration de radon a été mesurée dans les sous-sols qu’aux étages supérieurs. Des associations statistiquement significatives et négatives (p<0.05) ont été observées entre la densité/proximité des puits et les concentrations de radon. Cela a mis en avant que, dans l’échantillon, les régions présentant des densités de puits plus hautes étaient associées avec une concentration de radon plus faible, avec une différence de concentration de radon de 0.1% par puits additionnel dans un rayon de 10 km (I.C. 95% : 0.05 ; 0.20). Nous n’avons observé aucune association positive entre les mesures de densité/proximité des puits et les concentrations de radon. Les associations négatives retrouvées étaient principalement influencées par les mesures de radon réalisées en 1992, période durant laquelle l’exploitation gazière et pétrolière n’utilisait que très peu la fracturation hydraulique . Ainsi, il serait intéressant d’approfondir ce travail, en incluant un échantillon plus large et comprenant plus de données en milieu rural. Aussi, l’inclusion de covariables additionnelles pourrait mieux contrôler la contribution potentielle d’autres facteurs (p. ex. âge et état du bâtiment, type d’isolation et de ventilation, phase de l’exploitation gazière ou pétrolière lors de la mesure radon).

This thesis develops an optimal interpolation method that takes daily precipitation values collected from weather stations and produces precipitation estimates on a grid. The method, called Hybrid 2.0, combines EOF-based linear interpolation with the nearest-station method. Gridded monthly precipitation is first obtained via EOF, then distributed among days via nearest station. Hybrid 2.0 builds on an earlier method, called Hybrid 1.0, that applies an inverse-distance weighting method to obtain gridded monthly values. Hybrid 2.0 uses these monthly Hybrid 1.0 values as inputs when constructing EOF functions. The data used in this thesis were obtained from the Meteorological Service of Canada. Few weather stations were located in the northern and mountain regions of Alberta prior to 1950. As a result, the Hybrid 1.0 gridded results underestimate precipitation in these regions for that period. The main contribution of Hybrid 2.0 is a substantial reduction in this bias, obtained by implicitly taking topographic elevation into account. Bias reduction is achieved by extracting EOFs from Hybrid 1.0 output for 1951-2002, when many more stations were present in the northern and mountain regions. Hybrid 2.0 is shown to be more accurate in interpolating both monthly and daily precipitation in Alberta, when compared with Hybrid 1.0 and other methods. The thesis also provides detailed analyses of precipitation trends and droughts using the gridded Hybrid 2.0 daily values. Optimality of the selected EOF modes and sensitivity to data error in the EOF-based linear reconstruction are also discussed in this thesis. Agricultural uses of historical climate data have become extremely important. Applications include: enabling prompt, optimal decisions on market prices and disaster aid, designing future agricultural practices such as adaptation to climate and technology changes, and managing risks for agricultural producers and governments in areas such as drought monitoring. Many applications require a reliable interpolation technique to accurately reconstruct daily climate estimates onto grids of various resolutions. The gridded Hybrid 2.0 daily precipitation values produced by this thesis satisfy this requirement and can be used as inputs for many agricultural applications. / Applied Mathematics