Air Pollution Statistics in Policy Applications

  1. Gregory R. Bock Organizer and
  2. Jamie A. Goode
  1. Rognvald I. Smith

Published Online: 28 SEP 2007

DOI: 10.1002/9780470515600.ch13

Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy

Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy

How to Cite

Smith, R. I. (2007) Air Pollution Statistics in Policy Applications, in Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy (eds G. R. Bock and J. A. Goode), John Wiley & Sons, Ltd., Chichester, UK. doi: 10.1002/9780470515600.ch13

Author Information

  1. Institute of Terrestrial Ecology, Edinburgh Research Station, Bush Estate, Penicuik, Midlothian EH26 0QB, UK

Publication History

  1. Published Online: 28 SEP 2007

ISBN Information

Print ISBN: 9780471985402

Online ISBN: 9780470515600

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Keywords:

  • air pollution statistics;
  • air pollution policy;
  • sulfur dioxide emissions;
  • concentration maps;
  • nitrogen dioxide concentrations

Summary

This review of the role of air pollution statistics in environmental policy sets the UK current controls of sulfur emissions for health and environmental effects in a historical context. The use of critical loads and levels is discussed. The role of air pollution monitoring data in assessing achievement of a health effects air quality standard or predicting exceedance of a critical level or critical load on a national basis is reviewed with the level of monitoring and the interpolation of concentration data identified as important issues. The problems of spatial scale, the scarcity of data for model validation and the use of trends to identify model inadequacy are illustrated. The current statistical challenges in understanding air pollution processes and defining appropriate policies include quantification of uncertainty within complex models, problems of spatial scale and model validation, and development of monitoring strategies which balance the spatial (more sites) and temporal (better process understanding) aspects of the science alongside the balance between policy desire and monitoring practicality. An appropriate statistical goal is development of methodology to ensure appropriate derived data with sufficient accuracy are used for measuring policy achievement.