22nd CCE Workshop and 28th ICP M&M Task Force Meeting 16-19 April 2012, Warsaw, Poland Impact of climate changes on forest ecosystems sensitivity to atmospheric deposition of sulphur and nitrogen the case study of Poland Katarzyna Juda-Rezler, Magdalena Reizer (WUT) Wojciech Mill, Tomasz Pecka, Adrian Schlama (IEP)
Outline 1. Goals 2. Selected regions 3. Modelling tools & simulation periods 4. Projections 5. Conclusions 2
Goals Climate projections Projections of climate changes impact on: Deposition of sulphur and nitrogen Critical loads of acidity and nutrient nitrogen Exceedances of critical loads 3
Selected regions 4
Kampinos domain Mazovia-Podlasie natural-forest region The region represents: the lowest forest cover in Poland (19.6%) medium level of damage Kampinos National Park (UNESCO s biosphere reserve): 2 nd largest National Park in Poland The vicinity of Warsaw agglomeration A mix of sand dunes and marshes Forests over 70% of Park area Pine 3 reintroduced mammals species: Elk (Alces alces) European beaver (Castor fiber) Lynx (Lynx lynx) 5
Karkonosze domain Sudetes natural-forest region The region represents: the highest forest cover in Poland (38%) one of the highest levels of damage Mountain climatic zone Karkonosze National Park (UNESCO s biosphere reserve) National Park of Stołowe Mountains Spruce 6
Climate & AQ modelling domain Centered over Poland: Center: 52.00 N, 19.30 E 118 x 107 grid cells Resolution: 10 km Map projection: Lambert Conformal Conic BALTIC SEA 7
Climate & AQ modelling system Global Climate Model GCM ECHAM5 Meteorological model/ RegCM3 Topography Land use Interface Initial and Boundary Condition Emission model Total ozone CTM Source of Figure: Bernd C. Krüger, BOKU-Met CAMx 4.4 8
Climate & AQ modelling system @ 10 km ECHAM5 RegCM3 CAMx (Juda-Rezler et al., 2012) RegCM3 Regional Climate Model (ITCP Trieste, Italy) CAMx v. 4.40 the Comprehensive Air quality Model with extensions (ENVIRON Int. Corp., Novato, California) Biogenic emissions (isoprene and terpene) calculated by RegCM3-CAMx interface program Anthropogenic emissions: EMEP data/emil emission model Juda-Rezler K., Reizer M., Huszar P., Krüger B.C., Zanis P., Syrakov D., Katragkou E., Trapp W., Melas D., Chervenkov H., Tegoulias I., Halenka T., 2012. On the effect of climate change on regional air quality over central-eastern Europe: concept, evaluation and future projections. Climate Research. In press. 9
EMIL (EMIssion model) for Poland METEOROLOGICAL MODEL Structure follows the modular setup of the SMOKE model EMISSION SOURCES INVENTORY Input data: Population Industry Point sources characteristics Agricultural activity Transport activity Municipal activity Heating characteristics EMIL EMISSION MODEL Emission factors Spatiotemporal algorithms GRIDDED EMISSION LCP characteristics and emission LCP data for 220 stacks Area sources with 1 km x 1 km resolution Sector-dependent Polish specific emission factors Sector-specific monthly, daily and hourly emission factors Biogenic activity TERRAIN Topography & Land use Trapp W., Paciorek M., Paciorek M.K, Juda-Rezler K., Warchałowski A., Reizer M., 2010. Modelling of PM 10 and PM 2.5 Particulate Matter Air Pollution in Poland. In: Environmental Engineering III, eds.: Pawłowski L., Dudzińska M. & A. Pawłowski, Taylor & Francis Group, London 2010: 97 104 10
CLs modelling tools Simple Mass Balance Model, according to Mapping Manual (UBA, 2004) 1 km x 1 km Kampinos domain 2079 records Karkonosze domain 1798 records 11
Modelling set-up Climate simulations 1961 2000 2021 2050 2071 2100 AQ simulations 1991 2000 2041 2050 2091 2100 A1B SRES IPCC scenario (Nakicenovic et al., 2000) of future emissions of greenhouse gases GCM simulations Anthropogenic emission in all simulations kept constant 2000 CRU TS 1.2 data used to correct the scenario precipitation data Trend analysis: 1961 2100 (1991 2100) a linear continuity was assumed 12
Results
Temperature (1961 2100) y = 0.0367x + 7.2569 Start 7.3 C End 10.9 C y = 0.0372x + 5.7036 Start 5.7 C End 9.4 C 14
Precipitation (1961 2100) y = 0.6845x + 538.16 y = 0.7895x + 769.6 Start 538 mm a -1 End 606 mm a -1 Start 770 mm a -1 End 849 mm a -1 15
S deposition (1991 2100) y = -1.4432x + 574.05 Start 574 eq ha -1 a-1 End 531 eq ha -1 a y = 1.6852x + 369-1 Start 369 eq ha -1 a-1 End 420 eq ha-1 a-1 16
N deposition (1991 2100) y = 3.4419x + 815.89 Start 819 eq ha -1 a-1 End 919 eq ha -1 a y = 5.6508x + 693.57-1 Start 699 eq ha -1 a-1 End 864 eq ha-1 a-1 17
CLs (1961 2100) y = 2.8384x + 1607.3 Start 1607 eq ha -1 a-1 End 1891 eq ha-1 a-1 y = 2.8252x + 1417 Start 1417 eq ha -1 a-1 End 1700 eq ha-1 a-1 y = 0.4521x + 510.01 Start 510 eq ha -1 a-1 End 555 eq ha -1 a y = 0.3996x + 762.97-1 Start 763 eq ha -1 a-1 End 803 eq ha-1 a-1 18
Exceedance of CL max S (1991 2100) No significant changes in exceedances of CL max S for both domains: in general CL max S >> Dep(S) decrease in Dep(S) in Kampinos and small increase in Karkonosze significant increase in CL max S values 19
Exceedance of CL nut N (2091 2100) Kampinos domain Karkonosze domain 20
Exceedance of CL nut N (1991 2100) y = 2.0077x + 299.77 Start 299 eq ha -1 a-1 End 357 eq ha-1 a-1 y = 5.1845x + 50.814 Start 56 eq ha -1 a-1 End 206 eq ha-1 a-1 21
Conclusions
Conclusions (1) Climate projections show significant changes for both domains (1961-2100) increase of T (3.6 3.7 C) increase of Prec, bigger in Karkonosze ( 14 %) Projected climate changes enhance the tolerance of studied forest soils to acidifying and eutrophying deposition increase of CL max S for both domains ( 300 eq/ha/a) small increase of CL nut N for both domains ( 40 eq/ha/a) Climate-AQ projections show (1991 2100): significant increase of Dep(N) for both domains much smaller impact on Dep(S) increase in Karkonosze; decrease in Kampinos 23
Conclusions (2) The effect of projected climate changes on the ecosystem protection against eutrophication is negative simulations show increase of Ex(CL nut N), up to almost 4. fold for Karkonosze The effect of projected climate changes on the ecosystem protection against acidification is neutral simulations show small/no increase of Ex(CL max S), with no trend according to climate change 24
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Acknowledgements The work was supported by: 6. FP EU, project CECILIA: Central and Eastern Europe Climate Change Impact and Vulnerability Assessment, Contract GOCE 037005 Special thanks to Tomas Halenka & Michal Belda from Charles University (Prague, Czech Republic) Bernd C. Krüger from University of Natural Resources and Life Sciences (Vienna, Austria) Erika Coppola from the Abdus Salam International Centre for Theoretical Physics (ICTP, Trieste, Italy) The calculations made at WUT were carried out at the Academic Computer Center in Gdańsk (TASK), Poland, on a cluster supercomputer GALERA 26