1. Environmental Modelling, Security Measures and Decision Making Zahari Zlatev National Environmental Research Institute Frederiksborgvej 399, P. O. Box 358 DK-4000 Roskilde, Denmark zz@dmu.dk

2. CONTENTS n Two types environmental models n Critical levels established in EU n Critical levels and decision making n Critical levels and climatic changes n UNI-DEM – Mathematical Description n Numerical Treatment n Parallel Computations n Designing a Set of Scenarios n Some Results n Major Conclusions

3. Generic Formulation of an Air Pollution Model Using splitting: advantages and drawbacks

4. Applying splitting techniques Coupling the sub-models

5. Numerical treatment of the horizontal transport Need for faster but still sufficiently accurate methods 1. How to obtain the system of ODEs? 2. How to solve the system of ODEs? Explicit methods with a stability control

6. Numerical treatment of the chemical reactions Need for faster but still sufficiently accurate methods 1. No spatial derivatives 2. Non-linear and stiff system of ODEs 3. Extremely badly scaled 4. Implicit numerical methods

7. Numerical treatment of the vertical exchange Need for faster but still sufficiently accurate methods 1. P and H depend on the spatial discretization 2. Linear and stiff system of ODEs 3. Implicit numerical methods 4. This sub-model is cheaper than the other two

8. UNI-DEM Initializing the model: NX: 96, 288, 480 NY: NY = NX (rectangular domains) NZ: 1 or 10 (easy to put more layers) N_SPECIES: 35, 56, 168 (RADM2, RACM) N_CHUNKS: chunks for parallel runs N_REFINED: related to emissions, 0 or 1 N_YEAR: year (any year from 1989 to 2004)

9. Size of the involved matrices Discretization Equations Time-steps 96x96x10 3 225 600 35 520 96x96x10 3 225 600 35 520 288x288x10 29 030 400 106 560 480x480x10 80 640 000 213 120 Assumption: 35 chemical species are used Why refined grids are needed?

10. Nitrogen dioxide pollution in Europe

11. Nitrogen emissions in Denmark

12. NO2 pollution in Denmark (coarse grid)

13. NO2 pollution in Denmark (fine grid)

14. Variation of the numbers of “bad days”

15. Conclusions n Take the inter-annual variations into account: runs over long time periods (20-30 years) are necessary n It is not enough to use scenarios based only on variations of the anthropogenic emissions: the natural emissions are also important n Comparing only concentrations is not enough: quantities related to the concentrations and having damaging effects might vary very much even if the variations of the concentrations are small n Large sets of scenarios are to be used n The use of fine resolution discretization is highly desirable n A direct consequence of the above requirements: need for better and faster mathematical and computational tools (numerical methods, reordering the computations, parallel codes, efficient exploitation of computer grids) n Data assimilation might lead to some considerable improvements n Statistical and graphical representation of the results to make them easily understandable even for non-specialists

16. More details 1. ”Computational and Numerical Challenges in Environmental Modelling”, Elsevier, Amsterdam - Boston - Heidelberg -New York - Oxford - Paris - San Diego - Singapore - Sydney - Tokyo, 2006. 1. Z. Zlatev and I. Dimov: ”Computational and Numerical Challenges in Environmental Modelling”, Elsevier, Amsterdam - Boston - Heidelberg -New York - Oxford - Paris - San Diego - Singapore - Sydney - Tokyo, 2006. 2. Z. Zlatev et al.: “Impact of Climate Changes on Pollution Levels in Europe”, http://www.softasap.net/ips/climatic_scenarios_NATO.pdf http://www2.dmu.dk/atmosphericenvironment/Climate%20and%20Pollutionhttp://www2.dmu.dk/atmosphericenvironment/Climate%20and%20Pollution http://www2.dmu.dk/atmosphericenvironment/Climate%20and%20Pollution http://www2.dmu.dk/atmosphericenvironment/Climate%20and%20Pollution