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Geostatistical assessment of long term human exposure to air pollution

  • N. Jeannée
  • V. Nedellec
  • S. Bouallala
  • J. Deraisme
  • H. Desqueyroux
Conference paper

Keywords

Mean Square Error Stochastic Simulation Ordinary Kriging Variogram Model Health Impact Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. ADEME (2002) Classification and Criteria for Setting Up Air-Quality Monitoring Stations. ADEME Editions, Paris, p. 63Google Scholar
  2. APHEIS (2000) Air pollution and Health: a European Information System. Monitoring the Effects of Air Pollution on Public Health in Europe. Scientific report 1999-2000. DG SANCO G/2“Polution related diseases” program; p. 135Google Scholar
  3. Blond N (2002) Assimilation de données photochimiques et prévision de la pollution troposphérique. Thèse de doctorat de l’Ecole Polytechnique, Palaiseau, p. 204Google Scholar
  4. Chilès JP, Delfiner P (1999) Geostatistics: modelling spatial uncertainty, Wiley Series in Probability and Mathematical Statistics, p. 695Google Scholar
  5. Cressie N, Kaiser MS, Daniels MJ, Aldworth J, Lee J, Lahiri SN, Cox LH (1998) Spatial Analysis of particulate matter in an urban environment. In: Second European Conference on Geostatistics for Environmental Application, (eds Gomez-Hernandez JJ, Soares A, Froidevaux R), Kluwer Academic Publishers, 41–51Google Scholar
  6. Deraisme J, Jaquet O, Jeannée N (2002) Uncertainty management for environmental risk assessment using geostatistical simulations. In: Fourth European Conference on Geostatistics for Environmental Application, (eds Sanchez-Villa X, Carrera J, Gomez-Hernandez JJ), Kluwer Academic Publishers, 139–150Google Scholar
  7. Geovariances (2004) Isatis Software Manual, 5th Edition, Geovariances & Ecole des Mines de Paris, p. 710Google Scholar
  8. Isaaks EH, Srivastava RM (1989) An introduction to Applied Geostatistics, Oxford University Press, p. 561Google Scholar
  9. Lajaunie C (1993) L’estimation géostatistique non linéaire. Cours C-152, Centre de Géostatistique, Ecole des Mines de ParisGoogle Scholar
  10. Lajaunie C, Béhaxétéguy JP (1989) Elaboration d’un programme d’ajustement semia-utomatique d’un modèle de corégionalisation — Théorie. Technical report N21/89/G. ENSMP Paris, p. 6Google Scholar
  11. Lantuéjoul C (2002) Geostatistical Simulation-Models and Algorithms. Springer-Verlag, p. 256Google Scholar
  12. Matheron G (1973) The intrinsic random functions and their applications. Advances in Applied Probability, 5, 439–468Google Scholar
  13. Mosqueron L, Nedellec V, Desqueyroux H, Annesi-Maesano I, Le Moullec Y, Medina S (2003) PEP project “Transport-related health impacts and their costs and benefits with a particular focus on children”; The Hague Workshop Input Reports; State of the Art-Review of exposures and health effects from Epidemiological studies Focused on Children, p. 53Google Scholar
  14. Rivoirard J (1994) Introduction to disjunctive kriging and non-linear geostatistics. Oxford University Press, Oxford, p. 181Google Scholar
  15. Roth C, Bournel-Bosson C (2001) Mapping diffusive sampling results: including uncertainty and indirect information. International conference Measuring Air Pollutants by Diffusive Sampling, Montpellier, France, Sept. 26-28 2001Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • N. Jeannée
    • 1
  • V. Nedellec
    • 2
  • S. Bouallala
    • 3
  • J. Deraisme
    • 1
  • H. Desqueyroux
    • 3
  1. 1.GEOVARIANCESAvonFrance
  2. 2.Vincent Nedellec ConsultantsParisFrance
  3. 3.ADEME, Direction de l’Air et des Transports, Département AirParis Cedex 15France

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