AIR POLLUTION – MONITORING MODELLING AND HEALTH

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280 Air Pollution – Monitoring, Modelling and Health Morozov, V.A. (1984). Methods for Solving Incorrectly Posed Problems. Springer Verlag. ISBN 0387960597. Morozov, V. A., & Stessin M. (1992). Regularization Methods for Ill-Posed Problems. CRC Press. Muniz, W. B., Campos Velho, H. F. & Ramos, F. M. (1999). A comparison of some inverse methods for estimating the initial condition of the heat equation. Journal of Computational and Applied Mathematics, Vol. 103, pp.145-163. ISSN: 0377-0427 Muniz, W. B., Ramos, F. M. & Campos Velho H. F., (2000). Entropy- and Tikhonov-based Regularization Techniques Applied to the Backwards Heat Equation, Computres & Mathematics with Applications, Vol. 40, pp. 1071-1084. ISSN: 08981221. Paes, F. F., Campos Velho, H.F. de, & Ramos, F. M. (2010). Land fluxes for the biogeochemical cycles estimated by artificial neural networks, Inverse Problems, Design and Optimization Symposium. Proceedings in CD-Rom. Ramos, F. M. & Giovannini A. (1995). Résolution d'un problème inverse multidimensionnel de diffusion de la chaleur par la méthode des eléments analytiques et par le principe de l'entropie maximale. International Journal of Heat and Mass Transfer, Vol. 38, pp. 101-111. ISSN: 0017-9310. Ramos, F. M., Campos Velho, H.F. de, Carvalho, J.C. & Ferreira, N.J. (1999). Novel approaches on entropic regularization. Inverse Problems, Vol 15, No. 5, pp. 1139-1148. ISSN: 0266-5611. Roberti, D.R., Anfossi, D., Campos Velho, H.F. de, & Degrazia, G.A. (2005). Estimation of Location and Strength of the Pollutant Sources, Ciencia e Natura, pp. 131-134. ISSN: 0100-8307. Roberti D. R. (2005). Inverse Problems in Atmospheric Physics. D.Sc. Thesis, Federal University of Santa Maria. Roberti, D.R., Anfossi, D., Campos Velho, H.F. de, & Degrazia G.A. (2007). Estimation of Pollutant Source Emission Rate from Experimental Data, Il Nuovo Cimento, Vol. 30 C, No. 02, pp. 177-186. ISSN: 0369-3554. Rumelhart, D. E., G. E. Hinton, R. J. Willians (1986). Learning representations of backpropagation erros. Nature, Vol. 323, pp. 533-536. Shannon, C.E. & Weaver W. (1949). The Matemathical Theory of Communication. University of Illinois Press. Shiguemori, E. H., Campos Velho, H. F., & Silva J. D. S. Da, (2004). Generalized Morozov's principle. Inverse Problems, Design and Optimization Symposium, Vol. 2, pp. 290-298. Shi, Y. & Eberhart R. C. (1998). A modified particle swarm optimizer. Proceedings of the IEEE International Conference on Evolutionary Computation. pp. 69-73, IEEE Press, Piscataway, NJ (USA). Smith, R. T., Zoltani, C. K., Klem, G. J. & Coleman, M. W. (1991). Reconstruction of tomographic images from sparse data sets by a new finite element maximum entropy approach. Applied Optics, Vol. 30, pp. 573-582. ISSN: 0003-6935. Tarantola A. (1987). Inverse Problem Theory. Elsevier Science Publishers, Amsterdam. Tikhonov, A.N. & Arsenin V.I. (1977). Solutions of Ill-posed Problems, John Wiley & Sons. Thomson, D. J. (1987). Criteria for the selection of stochastic models of particle trajectories in turbulent flows, Journal of Fluid Mechanics, Vol. 180, pp. 529-556. Tsallis C. (1988). Possible generalization of Boltzmann-Gibbs statistics, Journal of Statistical Physics, Vol. 52, p. 479-487. ISSN: 0022-4715.
13 Methodology to Assess Air Pollution Impact on Human Health Using the Generalized Linear Model with Poisson Regression Yara de Souza Tadano 1 , Cássia Maria Lie Ugaya 2 and Admilson Teixeira Franco 2 1 State University of Campinas – Sao Paulo, Department of Mechanical Engineering 2 Federal University of Technology – Paraná, Department of Mechanical Engineering Brazil 1. Introduction The growth of urban areas increased the access to many facilities such as transportation, energy, education, water supply, etc. As a consequence, there was a vehicular and industrial growth that combined with unfavorable meteorological conditions caused several worldwide episodes of excessive air pollution with life losses and health damage. Some examples were the well known Donora disaster in October, 1948 and fog episodes occurred after December, 1952 in London (Lipfert, 1993). Since then, the researchers started to worry about air pollutants impact. Many epidemiological studies of air pollution have been conducted showing that air pollution affects human health, especially in respiratory and cardiovascular diseases, even where concentration levels of pollutants are below the air quality standard levels (Braga et al., 1999; Braga et al., 2001; Burnett et al., 1998; Ibald-Mulli et al., 2004; Peng et al., 2006; Peters et al., 2001; Pope III et al., 2002; Samet et al., 2000a, 2000b). The evaluation of the impact of air pollution on human health is complex due to the fact that several personal characteristics (age, genetics, social conditions, etc.) influence on the response to a given air pollutant concentration. For instance, several studies have shown that a higher air pollution concentration increases the number of respiratory diseases in elderly and children (Braga et al., 1999; Braga et al., 2001). These studies show that children are more susceptible because they need twice the amount of air inhaled by adults and the elderly are more affected due to their weak immune and respiratory systems in addition to the fact they have been exposed to a great amount of air pollution throughout their lives. Another characteristic is genetics. The studies showed that people with chronic diseases or allergies, such as bronchitis and asthma are more sensitive to air pollution. In this chapter, it will be presented a summary of four kinds of studies usually used to assess air pollution impact on human health and emphasizing the most used one: the time
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AIR POLLUTION - MONITORING, MODELLI
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Contents Preface IX Chapter 1 Urban
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Preface This book provides a compre
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