AIR POLLUTION – MONITORING MODELLING AND HEALTH

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116 Air Pollution – Monitoring, Modelling and Health Unal, Y.S.; Deniz, A.; Toros, H. & Incecik, S. (2011). Influence of Meteorological Factors and Emission Sources on Spatial and Temporal Variations of PM 10 Concentrations in Istanbul Metropolitan Area, Atmospheric Environment, Vol.45, pp. 5504-5513. UNEP United Nations Environment Program, Urban Environment Unit. United Nations Environment Programme/Global Environmental Monitoring System. Urban Air Pollution; Environmental Library No.4, Oxford, England, 1991. Visschedijk, M.; Hendriks, R. & Nuyts, K. (2005). How to Set up and Manage Quality Control and Quality Assurance, The Quality Assurance Journal, Vol.9, pp. 95 – 107. Wang, H.; Fu, L.; Zhou, Y.; Du, X. & Ge, W. (2010). Trends in Vehicular Emissions in China’s Mega Cities from 1995 to 2005, Environmental Pollution, Vol.158, pp. 394–400. WHO, (2008). Air Quality and Health, Fact Sheet N°313 WHO, (2009). Center for Health Development, World Health Organization Centre for Health Development (WHO Kobe Centre – WKC) Wu, Z.; Hu, M.; Lin, P.; Liu, S.; Wehner, B. & Wiedensohler, A. (2008). Particle Number Size Distribution in the Urban Atmosphere of Beijing, China, Atmospheric Environment, Vol.42, pp. 7967-7980. Zakey, A.S.; Abdelwahab, M.M.; Pattersson, J.J.C.; Gatari, M.J. & Hallquist, M. (2008). Seasonal and Spatial Variation of Atmospheric Particular Matter in a Developing Megacity, the Greater Cairo, Egypt Atmosfera, Vol.21, pp. 171-189. Zhao,P (2010). Sustainable Urban Expansion and Transportation in a Growing Megacity: Consequences of Urban Sprawl for Mobility on the Urban Fringe of Beijing, Habitat International, Vol.34, pp. 236–243. Zhou, K.; Ye, Y-H.; Liu, Q.; Liu, A-J. &Peng, S-L. (2007). Evaluation of Ambient Air Quality in Guangzhou, China, Journal of Environmental Sciences, Vol.19, pp. 432-437. Zhu, L.; Huang, X.; Shi, H.; Cai, X. & Song, Y. (2011). Transport Pathways and Potential Sources of PM 10 in Beijing, Atmospheric Environment, Vol.45, pp. 594-604.
5 Air Pollution Monitoring Using Earth Observation & GIS Diofantos G. Hadjimitsis, Kyriacos Themistocleous and Argyro Nisantzi Cyprus University of Technology Cyprus 1. Introduction Air pollution has received considerable attention by local and global communities (Wald et al, 1999). Many major cities have established air quality monitoring stations but these stations tend to be scarcely distributed and do not provide sufficient tools for mapping atmospheric pollution since air quality is highly variable (Wald et al, 1999). Satellite remote sensing is a valuable tool for assessing and mapping air pollution as satellite images are able to provide synoptic views of large areas in one image on a systematic basis due to the temporal resolution of the satellite sensors. Blending together earth observation with ground supporting campaigns enables the users or governmental authorities to validate air pollution measurements from space. New state-of-the-art ground systems are used to undertake field measurements such as Lidar system, automatic and hand held sunphotometers etc. The rise of GIS technology and its use in a wide range of disciplines enables air quality modellers with a powerful tool for developing new analysis capability. Indeed, thematic air pollution maps can be developed. Moreover, the organization of data by location allows data from a variety of sources to be easily combined in a uniform framework. GIS provides the opportunity to fill the technical gap between the need of analysts and decision-makers for easy understanding of the information. This Chapter presents an overview of how earth observation basically is used to monitor air pollution through on overview of the existing ground and space systems as well through the presentation of several case studies. 2. Relevant literature review The use of earth observation to monitor air pollution in different geographical areas and especially in cities has received considerable attention (Kaufman and Fraser, 1983; Kaufman et al., 1990; Sifakis and Deschamps, 1992; Retalis, 1998; Retalis et al., 1998; Sifakis et al., 1998; Retalis et al., 1999; Wald and Balleynaud, 1999; Wald et al., 1999; Hadjimitsis et al., 2002; Themistocleous et al., 2010; Nisantzi et al. 2011; Hadjimitsis et al., 2011). All the studies have involved the determination of aerosol optical thickness (AOT) either using indirect methods using Landsat TM/ETM+, ASTER, SPOT, ALOS, IRS etc. images or MODIS images in which AOT is given directly. The superior spatial resolution of Landsat and SPOT enable several researchers to develop a variety of methods based on the radiative transfer equation,
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Preface This book provides a compre
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