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Thoughts after Friday's (3 March 2000, Imperial College, London) EURASAP Committee Meeting

Future of Air Pollution Science

I found Friday's meeting very useful even though I may have been slow to pick up a theme going through all our work.

We generally acknowledged that many of the major issues of air quality were solved, or could be solved, by adopting a source reduction approach. There are no doubt neglected areas but these can be tackled using current techniques. These problems will provide continued work in the consultancy area. However for new, challenging problems Peter argued that we should look at issues associated with climate, since this could not go away. The singular difficulty with environmental problems is that one is required to base decisions on predictions, which cannot be fully tested. There are numerous examples, including climate, acid rain, very infrequent but potentially catastrophe nuclear releases etc. There are not laboratory scale tests for many (most?) environmental systems.

Therefore it seems to me that at the beginning of the 21st Century we are faced with limits to prediction, which should not be forgotten, even though techniques and methods have advanced enormously over the last 100 years. The 3D Eulerian transport model, or the climate model, represents an enormous advance on what has gone before but it does not represent perfect reality. This may take the form of not being able to establish low-level health effects or not being able to incorporate real inhomogeneities in the real world. All predictions include some error or fuzziness. The most interesting challenge to the air quality community is tackling the "limit to prediction". We should be looking at methods, which can establish more accurately what these limits might be. The limits should be judged only after making the maximum use of both measurements and models. We should perhaps move away from the traditional approach of comparing predictions with observations, judging that a model does quite well and then applying the model well beyond the range over which it has been tested.

The "limit to prediction" problem is not unique to air pollution science. However air quality presents a special wealth of examples of environmental systems which can be use as case studies for estimating predictability. There must be a range of techniques available from recent software engineering/computer science. Is this a topic for a joint research activity between us all, if only in our spare time if we had any? We could also look at the how far predictions have been fulfilled, once large scale changes in emissions have taken place e.g. acid deposition.

Finally there is the issue of translating the "limit of prediction" to the policy maker. Should weather forecasters still be set targets for improving predictions or are there other ways of incorporating uncertainty e.g. degrees of precaution etc. Any thoughts?

Bernard
Many thanks to Helen for her hospitality.

Contact:
Prof. Bernhard Fisher
School of Earth and Environmental Sciences
University of Greenwich, Chatham Maritime
Medway Campus, Kent ME4 4AW, United Kingdom
Tel: +44 81 316 9911, Fax: +44 81 316 9805
E-mail:
B.E.A.Fisher@greenwich.ac.uk
       
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