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Magic,Safe and Smart Model Applications at Integrated Monitoring Sites: Effects of Emission Reduction Scenarios
Authors:Forsius  M.  Alveteg  M.  Jenkins  A.  Johansson  M.  Kleemola  S.  Lükewille  A.  Posch  M.  Sverdrup  H.  Walse  C.
Affiliation:1. Finnish Environment Institute, P.O.Box 140, FIN-00251, Helsinki, Finland
2. Chemical Engineering II, Lund University, P.O.Box 124, S-22 100, Lund, Sweden
3. Institute of Hydrology, Wallingford, OXON, Oxfordshire, OX10 8BB, United Kingdom
4. Norwegian Institute for Air Research, P.O.Box 100, N-2007, Kjeller, Norway
5. RIVM, P.O.Box 1, NL-3720 BA, Bilthoven, The Netherlands
Abstract:Three well-known dynamic acidification models (MAGIC, SAFE, SMART) were applied to data sets from five Integrated Monitoring sites in Europe. The calibrated models were used in a policy-oriented framework to predict the long-term soil acidification of these background forest sites, given different scenarios of future deposition of S and N. Emphasis was put on deriving realistic site-specific scenarios for the model applications. The deposition was calculated with EMEP transfer matrices and official emissions for the target years 2000, 2005 and 2010. The alternatives for S deposition were current reduction plans and maximum feasible reductions. For N, the NOx and NHy depositions were frozen at the present level. For NOx, a reduction scenario of flat 30% reduction from present deposition also was utilized to demonstrate the possible effects of such a measure. The three models yielded generally consistent results. The ‘Best prediction’-scenario (including the effects of the second UN/ECE protocol for reductions of SO2 emissions and present level for NOx-emissions), resulted in many cases in a stabilization of soil acidification, although significant improvements were not always shown. With the exception of one site, the ‘Maximum Feasible Reductions’ scenario always resulted in significant improvements. Dynamic models are needed as a complement to steady-state techniques for estimating critical loads and assessing emission reduction policies, where adequate data are available.
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