Environmental Modelling, Security Measures and Decision Making

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Environmental Modelling, Security Measures and
Decision Making

• Zahari Zlatev
• National Environmental Research Institute
• Frederiksborgvej 399, P. O. Box 358
• DK-4000 Roskilde, Denmark
• zz_at_dmu.dk

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CONTENTS

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

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Generic Formulation of an Air Pollution Model
Using splitting advantages and drawbacks
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Applying splitting techniques
Coupling the sub-models
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Numerical treatment of the horizontal transport
1. How to obtain the system of ODEs? 2. How to
solve the system of ODEs? Explicit methods with a
stability control
Need for faster but still sufficiently accurate
methods
6
Numerical treatment of the chemical reactions
1. No spatial derivatives 2. Non-linear and stiff
system of ODEs 3. Extremely badly scaled 4.
Implicit numerical methods
Need for faster but still sufficiently accurate
methods
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Numerical treatment of the vertical exchange
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
Need for faster but still sufficiently accurate
methods
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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)

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Size of the involved matrices

• Discretization Equations Time-steps
• 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?

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Nitrogen dioxide pollution in Europe
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Nitrogen emissions in Denmark
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NO2 pollution in Denmark (coarse grid)
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NO2 pollution in Denmark (fine grid)
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Variation of the numbers of bad days
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Conclusions

• Take the inter-annual variations into account
  runs over long time periods (20-30 years) are
  necessary
• It is not enough to use scenarios based only on
  variations of the anthropogenic emissions the
  natural emissions are also important
• 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
• Large sets of scenarios are to be used
• The use of fine resolution discretization is
  highly desirable
• 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)
• Data assimilation might lead to some considerable
  improvements
• Statistical and graphical representation of the
  results to make them easily understandable even
  for non-specialists

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More details

• 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.
• Z. Zlatev et al. Impact of Climate Changes on
  Pollution Levels in Europe,
• http//www.softasap.net/ips/climatic_sce
  narios_NATO.pdf
• http//www2.dmu.dk/atmosphericenvironment/Climate
  20and20Pollution