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(Further) (Possible) ICP M&M Contribution to Integrated Assessment Maximilian Posch

(Further) (Possible) ICP M&M Contribution to Integrated Assessment Maximilian Posch Jean-Paul Hettelingh, Jaap Slootweg Coordination Centre for Effects (CCE) ICP Modelling & Mapping Bilthoven, Netherlands www.pbl.nl/cce. Integrated Assessment (IA) under the LRTAP Convention

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(Further) (Possible) ICP M&M Contribution to Integrated Assessment Maximilian Posch

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  1. (Further) (Possible) ICP M&M Contribution to Integrated Assessment Maximilian Posch Jean-Paul Hettelingh, Jaap Slootweg Coordination Centre for Effects (CCE) ICP Modelling & Mapping Bilthoven, Netherlands www.pbl.nl/cce

  2. Integrated Assessment (IA) under the LRTAP Convention • Generally carried out under TFIAM • Done with the GAINS model by CIAM • … mostly minimizing costs for an accepted reduction target • for an agreed set of environmental and human health indicators • Making use of (the linearized version of) the EMEP • atmospheric chemistry and transport model(s) • New (and ‘welcomed’ by WGSR and EB): • Ex-post analyses by the WGE-ICPs of (selected) scenarios • (in collaboration with EMEP and CIAM)

  3. Scheme for CCE [ex-post] analyses (see SR2008): Modelling: SMB, Dynamic Modelling, … Empirical CLs, Dose-Response Functions, …

  4. Steps in analysis (with emphasis on ICP M&M) 1. Receive scenario from CIAM (in form of country emissions of S, NOx, NH3, …) 2. Obtain deposition fields by … a) using the linearised EMEP model b) convincing EMEP to run the Unified Model for the given scenario 3. Analyse: a) compute various indicators b) compare with existing (reference) scenarios c) summarise and display results [in familiar and novel ways] 4. Report back to TFIAM/WGSR

  5. Data and models available • Official 2008 Critical Loads data base • (modelled & empirical; but also earlier versions) • European Background CL data base (EU-DB): • To fill in gaps, but also for ‘experimental’ work • NFC dynamic modelling output: • 7 variables for 14 scenarios in 9 reference years • VSD modelling results (using EU-DB): • To fill gaps and for experiments/investigations • … and … • Linearised version of the EMEP model: • for annual average S, NOx and NH3 deposition (only) • - Other EMEP model output; e.g. concentration fields

  6. Example: Exceedance of acidity CLs Note: Also %area exceeded indicated! Other forms: a) Maps of exceeded area b) Country Tables of exceedances/ exceeded area c) CDFs d) ……

  7. Example: Exceedance of (computed) nutrient N CLs Other forms: see above … What’s presented so far, can also be computed/shown by CIAM (albeit less beautiful!)

  8. Example: Exceedance of empirical CLs (for nutrient N) Grassland Scrubs Forests 1990 CLE 2020 MFR 2020 [Fig6-1]

  9. Example: Comparing the exceedance of empirical and computed CLnutN’s (‘ensemble assessment’) In every EMEP grid cell compare % ecosystem area exceeded for both CL-types and assign ‘likelihood’ of exceedance according to Fig, using IPCC lingo … % area exceeded of computed CLnutN p1*p2=const % area exceeded of empirical CLnutN

  10. Example: Mapping Ensemble Assessment Prerequisite: Data for both available …..

  11. Examples: Dynamic Modelling: Damage and Recovery Delay Times (DDT and RDT)

  12. Example: Dynamic Modelling: Target Loads & Delay Times

  13. Example: Dynamic Modelling Data Dynamic Modelling output obtained/produced for: 7 variables: [Al], [Bc], pH, [ANC], bsat, C:N ratio, [N] … in the following 9 years: History: 1980, 1990, 2000, 2010 … once; and Future: 2020, 2030, 2040, 2050, 2100 … for 14 deposition scenarios [ 7 x (4 + 5 x 14) = 518 values per site] Results for arbitrary scenario obtained by interpolation!

  14. Example: Target Loads of N acidity in 2050 CLmax(N) TLmax(N) Black dot in square: also infeasible TLs!

  15. Example: Non-achievement (‘violation’) of nutrient-N Target Loads Exceedance of CLnutN Violation of 2050-TLnutn 49 % area violated (AAE >0) 48 % area exceeded (AAE > 0)

  16. Example: Exceedance of Critical Levels • 2005/06: Update of critical • level for NH3 concentration: • - Lichens & bryophytes: • 1 µg NH3/m3 • Herbaceous plants: • 3±1µg NH3/m3(was 8) Reference: Cape JN, Van der Eerden LJ, Sheppard LJ, Leith ID, Sutton MA (2009) Evidence for changing the critical level for ammonia. Environmental Pollution 157: 1033-1037

  17. Example: Exceedance of CLnutN with zero NOx and NH3 emissions AAEnut, 2010 NOx = 0 AAEnut, 2010 AAEnut, 2010 NH3 = 0 Caveats!

  18. Example: Consequences of ‘equitable’ emission reductions Sorted S and N emission densities (tS|N/km2): S total N NOx-N NH3-N MT 18.552 MT 9.402 MT 5.670 MT 3.731 BG 4.410 NL 5.837 LU 3.259 NL 3.230 BA 4.012 LU 5.161 NL 2.607 BE 2.146 MD 1.727 BE 4.466 BE 2.320 LU 1.901 PL 1.682 DK 2.695 GB 1.350 DK 1.617 BE 1.617 DE 2.458 DK 1.078 IE 1.531 MK 1.615 GB 2.436 IT 1.016 DE 1.446 HU 1.430 IT 2.166 DE 1.013 CH 1.245 Red = S Blue = NOx-N Green = NH3-N Black = Total N

  19. Example: Equitable emission reductions and nutrient N exceeded ecosystem area Green horizontal lines: 10%, 25% (top), 50% (solid), 75%, 90% (bottom) European NH3 emission reduction. Black vertical lines: same for Eurpean NOx emission reductions (right to left). For every max. emission density of NOx and NH3 the % European ecosystem area exceeded can be seen and the corresponding % European emission reductions

  20. Example: Equitable emission reductions and acidity CL exceeded ecosystem area Red horizontal lines: 10%, 25% (top), 50% (solid), 75%, 90% (bottom) European S emission reduction. Black vertical lines: same for European N emission Reductions (right to left) For every max. emission density of N and S the % European ecosystem area exceeded can be seen and the corresponding % European emission reductions

  21. Example (cont’d): Reducing European emissions by 50% (S and N) in this equitable way would require the following reductions in individual countries: S: NOx: NH3: MT 94.8% MT 76.7% MT 84.5% BG 78.2% NL 73.1% NL 75.0% BA 76.1% BE 59.6% LU 71.7% MD 44.4% LU 54.3% BE 67.3% PL 42.9% DK 46.3% DK 45.8% BE 40.6% IE 43.3% DE 40.6% MK 40.5% DE 39.9% GB 40.1% HU 32.9% CH 30.3% IT 32.6% RO 31.8% IT 24.5% IE 25.7% CS 29.3% FR 21.4% CH 17.5% TR 12.3% MD 20.3% FR 14.7% GB 20.0% MD 12.6% RO 12.1% PL 0.7% BG 5.3% Countries not in column  no reduction Remarks: (a) Not effects-based! (b) Interesting, but probably difficult to agree upon … (c) Linearised EMEP model stretched to limit! (d) Similar examples easy to investigate

  22. Further Examples: • e.g. • Influence of climate change on Critical Loads • (and dynamic model results) • Influence of land cover changes on CLs • More detailed modelling of biodiversity (changes) • (on Natura 2000 and other protected areas) • - ….. … and so on … and so on …

  23. Conclusions: A variety of ex-post analyses can be carried out by the ICP M&M with respect to: - the exceedance of Critical Loads and Levels (N&S) - the state and timing of chemical recovery with the aid of Dynamic Modelling (results) - preliminary biodiversity assessments using empirical critical loads, dose-response functions Important are contributions by other ICPs to make full use of the WGE’s accumulated potential and knowledge.

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