R.J. Wichink Kruit 1, D. Simpson 2, M. Schaap 1, R. Kranenburg 1, E. Dammers 1, C.A. Geels 3, C. Skjoth 4, M. Engardt 5, A. Graff 6, R. Stern 7, B. Bessagnet.

Slides:



Advertisements
Similar presentations
Integrated modelling and monitoring for use in forecasting Jørgen Brandt and Finn Palmgren National Environmental Research Institute Department of Atmospheric.
Advertisements

Ozone Assimilation in the Chemistry Transport Model CHIMERE using an Ensemble Kalman Filter (EnKF) : Preliminary tests over the Ile de France region 2.
ACCENT-plus Symposium, Urbino 2013 The effect of climate and climate change on ammonia emissions in Europe Camilla Geels 1 and Carsten Ambelas Skjøth 2.
Fighting the Great Challenges in Large-scale Environmental Modelling I. Dimov n Great challenges in environmental modelling n Impact of climatic changes.
Inputs from the PROMOTE/MACC projects Laurence Rouïl (INERIS)
Title EMEP Unified model Importance of observations for model evaluation Svetlana Tsyro MSC-W / EMEP TFMM workshop, Lillestrøm, 19 October 2010.
G. Pirovano – CESIRICERCA, Italy Comparison and validation of long term simulation of PM10 over 7 European cities in the frame of Citydelta project Bedogni.
Atmospheric modelling activities inside the Danish AMAP program Jesper H. Christensen NERI-ATMI, Frederiksborgvej Roskilde.
TNO experience M. Schaap, R. Timmermans, H. Denier van der Gon, H. Eskes, D. Swart, P. Builtjes On the estimation of emissions from earth observation data.
15 / 05 / 2008 Model ensembles for the simulation of air quality over Europe Robert Vautard Laboratoire des Sciences du Climat et de l’Environnement And.
Improving regional air quality model results at the city scale : results from the EC4MACS project INERIS : Bertrand Bessagnet, Etienne Terrenoire, Augustin.
PREV ’AIR : An operational system for air quality monitoring and forecasting Laurence ROUÏL.
The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W.
1 1 Model studies of some atmospheric aerosols and comparisons with measurements K. G e o r g i e v I P P – B A S, S o f i a, B u l g a r i a.
TFMM & TFEIP Workshop, Dublin, 2007 Uncertainties of heavy metal pollution assessment Oleg Travnikov EMEP/MSC-E.
ICDC7, Boulder, September 2005 CH 4 TOTAL COLUMNS FROM SCIAMACHY – COMPARISON WITH ATMOSPHERIC MODELS P. Bergamaschi 1, C. Frankenberg 2, J.F. Meirink.
Modelling of Acid deposition in South Asia Magnuz Engardt Swedish Meteorological and Hydrological Institute (SMHI) Introduction to Acid deposition.
Modelled results vs. emission estimates S.Dutchak, I.Ilyin, O.Travnikov, O.Rozovskaya, M.Varygina EMEP/MSC-East Modelled results vs. emission estimates.
Diurnal cycles of fossil fuel CO 2 : Comparison of model results with observations at Heidelberg and Schauinsland Felix Vogel 1 including work of: I. Levin.
O. Russell Bullock, Jr. National Oceanic and Atmospheric Administration (NOAA) Atmospheric Sciences Modeling Division (in partnership with the U.S. Environmental.
Contact: Vigdis Vestreng This study is funded by the EMEP Trust Fund, the European Commission’s Fifth Framework program CARBOSOL Project (contract No.
The Euro- and City-Delta model intercomparison exercises P. Thunis, K. Cuvelier Joint Research Centre, Ispra.
EEA-PROMOTE users meeting, Copenhagen, 12 June 2008 Laurence Rouïl, Vincent-Henri Peuch, Anthony Ung Hendrik Elbern, Achim Strunk Thilo Erbertseder, Thomas.
8th meeting of the TFEIP’s projections expert panel, 15th May 2012 Bern, Switzerland. Emissions projections reported under the LRTAP convention and EEA.
Closing the Global Bomb Radiocarbon Budget Tobias Naegler 1,2, Vago Hesshaimer 1, and Ingeborg Levin 1 1 Institut für Umweltphysik, Universität Heidelberg,
Gloream workshop, Paris 2006 Setting of an experimental forecast system for air quality at ECMWF in the framework of the GEMS project : implementation.
Eskes, TROPOMI workshop, Mar 2008 Air Quality Forecasting in Europe Henk Eskes European ensemble forecasts: GEMS and PROMOTE Air Quality forecasts for.
Intercomparison of Mesoscale and Global Atmospheric Transport Models over Western Europe P. Ciais2), A.T. Vermeulen1), C. Geels3), P. Peylin2), M. Gloor4),
13 / 10 / 2006 Uncertainty and regional air quality model diversity: what do we learn from model ensembles? Robert Vautard Laboratoire des Sciences du.
EMEP WGSR, EMEP Progress on HMs, 2006  Review and evaluation of the MSCE-HM model (TFMM)  Atmospheric pollution in 2004 (emissions, monitoring.
29 th TF meeting of the ICP-Vegetation, March, 2016, Dubna, Russia ANALYSIS OF LONG-TERM TRENDS OF ATMOSPHERIC HEAVY METAL POLLUTION IN THE EMEP COUNTRIES.
17 th TFMM Meeting, May, 2016 EMEP Case study: Assessment of HM pollution levels with fine spatial resolution in Belarus, Poland and UK Ilia Ilyin,
The application of Models-3 in national policy Samantha Baker Air and Environment Quality Division, Defra.
Evaluation of pollution levels in urban areas of selected EMEP countries Alexey Gusev, Victor Shatalov Meteorological Synthesizing Centre - East.
National Environmental Research Institute, University of Aarhus, Denmark Impacts of climate change on air pollution levels in the Northern Hemisphere G.
Norwegian Meteorological Institute
Progress in 2017 Work-plan elements
Joint thematic session: from hemispheric to local scale air pollution; Twin Site project Task Force on Measurements and modelling A. Colette (TFMM),
Joint thematic session on B(a)P pollution: main activities and results
The CAMS Policy products
REanalysis of the TROpospheric chemical
SHERPA for e-reporting
Progress in assessment of POP pollution in EMEP region.
AQMEII3: the EU and NA regional scale program of the Hemispheric Transport of Air Pollution Task Force The AQMEII 3 modelling team S. Galmarini, C. Hogrefe,
Heavy metal pollution assessment within EMEP
Changes to the methodology since the NEC report #2
POPs and HMs Summary , EMEP TFMM.
A. Aulinger, V. Matthias, M. Quante, Institute for Coastal Research
Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulyh
The EuroDelta project - Sectoral approach to IAM -
EURODELTA III RCG-Model
Multi-model and Observed PM Trends
EMEP Case study: Assessment of HM pollution levels with fine spatial resolution in Belarus, Poland and UK Ilia Ilyin, Olga Rozovskaya, Oleg Travnikov.
17th Task Force on Measurement and Modelling Meeting
EURODELTA 3 – Trend Analysis
Inverse modeling of European sources:
Jan Eiof Jonson, Peter Wind EMEP/MSC-W
CITY-DELTA Objectives, Methodology, and Results
EURODELTA Preliminary results
Progress and problems of POP modelling
Uncertainties of heavy metal pollution assessment
Air Quality Evaluation International Initiative (AQMEII)
The EuroDelta inter-comparison, Phase I Variability of model responses
Model uncertainties because of inconsistencies of emissions
Modelling air quality at high resolution in the Netherlands with plume and grid models Eric van der Swaluw1, Wilco de Vries1, Jan Aben1, Ferd Sauter1,
A Visualization/Analysis Tool for Model - to – Observations/Emissions
Model assessment of HM and POP pollution of the EECCA region
tackling hemispheric transport of air pollutants work at the JRC
Modelling of BaP concentrations over France.
J.M. Baldasano, M.T. Pay, S. Mailler, P. Jiménez, S. Gassó
Presentation transcript:

R.J. Wichink Kruit 1, D. Simpson 2, M. Schaap 1, R. Kranenburg 1, E. Dammers 1, C.A. Geels 3, C. Skjoth 4, M. Engardt 5, A. Graff 6, R. Stern 7, B. Bessagnet 8, L. Rouil 8, J.M. Baldasano 9, M. Pay 9, D. Hauglustaine 10, A. Nyiri 2, M.A. Sutton 11, S. Reis 11, P. Thunis 12 and C. Cuvelier 12 ÉCLAIRE model inter-comparison of atmospheric nitrogen deposition and concentrations over Europe 1 TNO, Dept. of Climate, Air and Sustainability, P.O. Box 80015, NL-3508TA Utrecht, The Netherlands 2 Norwegian Meteorological Institute, Air Pollution Section Research Department, P.O. Box 43, Blindern, N-0313, Oslo, Norway 3 Aarhus University, Department of Environmental Science-Atmospheric modeling, Frederiksborgvej 399, 4000 Roskilde, Denmark 4 University of Worcester, National Pollen and Aerobiology Research Unit, Henwick Grove, VR2 6AJ, Worcester, United Kingdom 5 SMHI, Norkoping 6 Umweltbundesamt, Postfach 1406, D Dessau-Roßlau, Germany 7 Freie Universität Berlin, Institut für Meteorologie und Troposphärische Umweltforschung, Carl-Heinrich-Becker Weg 6-10, D Berlin, Germany 8 INERIS, Institut National de l’Environnement Industriel et des Risques Parc Technologique, ALATA, F Verneuil-en-Halatte, France 9 Barcelona Supercomputing Center, c/ Jordi Girona 29, E Barcelona, Spain 10 Laboratoire des Sciences du Climat et de l’environnement, UMR 8212 CEA-CNRS-UVSQ, Gif-sur-Yvette, France 11 CEH, Natural Environmental Research Council, Bush Estate, Pinicuik, Midlothian, EH26 0QB 12 European Commission, DG Joint Research Centre, Institute for Environment and Sustainability, I Ispra (Va), Italy

Motivation It is difficult to say anything about uncertainties in model calculations of Nr-deposition as there are no observations of total Nr deposition available yet. This study aims to: deliver an ensemble map of the total Nr-deposition over Europe based on 7 regional European CTMs, and to estimate the inter-model variation in the total Nr-deposition over Europe validate the models by comparing modelled wet depositions and concentrations with observations from the EMEP wet deposition network and NitroEurope IP

Model settings ECLAIRE model comparison Modelling the European Nitrogen budget 3 DomainnxnyΔLon ( °) ΔLat ( °) ΔLon x ΔLat (km x km) SW corner grid centre (Lon / Lat) Europe x 28 (N) 44 x 28 (S) / Emissions: provided by INERIS at 0.5° x 0.25° Longitude/Latitude Note: INCA used own emissions! Other Input: not prescribed. Output domain: Resolution: 0.5° x 0.25° (~28x28 km 2 ) DEHM: hemispheric (~ 50x50 km 2 ) INCA (global): 3.75° x 1.875° (~210x210 km 2 ) Models: EMEP, LOTOS-EUROS, DEHM, MATCH, CMAQ, CHIMERE, RCGC, INCA (global)

Individual model results ECLAIRE model comparison Modelling the European Nitrogen budget 4 EMEP CMAQ CHIMERE RCGC MATCHLOTOS- EUROS DEHM INCA dry NHx dry NOy wet NHx wet NOy

Ensemble of 7 regional CTMs: Total Nr ECLAIRE model comparison Modelling the European Nitrogen budget 5

Contribution of NHx to total Nr ECLAIRE model comparison Modelling the European Nitrogen budget 6

10-day running mean of model domain Total Nr ECLAIRE model comparison Modelling the European Nitrogen budget 7 Dry Nr ~ 40% Wet Nr ~ 60%

Contribution of dry Nr to total Nr ECLAIRE model comparison Modelling the European Nitrogen budget 8

ECLAIRE model comparison Modelling the European Nitrogen budget 9 10-day running mean of model domain Dry NOy ~ 35% Wet Noy ~ 65% Dry NHx ~ 45% Wet NHx ~ 55%

Conclusions from model inter-comparison This study showed that the total Nr-deposition (NHx +NOy) in the model domain were rather similar in all models The variation in model results is largest for the dry deposition of NHx Larger dry deposition is compensated by smaller wet deposition The average variation in the modeled Nr-deposition was about 30-50% over land and % over water NHx vs. NOy deposition is approximately 50% vs. 50%, but large regional differences! Dry versus wet deposition contributions are approximately 45% vs. 55% for NHx and 35% vs. 65% for NOy and 40% vs. 60% for total Nr (but large regional differences again!) KLD presentatie 24-maart 2011 Development of GHG projection guidelines 10

Comparison with EMEP wet deposition and NitroEurope IP observation ECLAIRE model comparison Modelling the European Nitrogen budget 11

Wet NHx [mg/m 2 ] wet NHxOBSERVED LOTOS- EUROSEMEPRCGCCMAQCHIMEREDEHMMATCHINCAENSEMBLE average stdev r bias rel. bias N68

Wet NOy [mg/m 2 ] wet NOyOBSERVED LOTOS- EUROSEMEPRCGCCMAQCHIMEREDEHMMATCHINCAENSEMBLE average stdev r bias rel. bias N68

NH 3 ECLAIRE model comparison Modelling the European Nitrogen budget 14 EMEP CMAQ CHIMERE RCGC MATCH LOTOS- EUROS DEHM INCA ENSEMBLE

NH 3 ECLAIRE model comparison Modelling the European Nitrogen budget 15 NH3OBSERVED LOTOS- EUROSEMEPRCGCCMAQCHIMEREDEHMMATCHINCAENSEMBLE average stdev r bias rel. bias N51

Conclusions from comparison with observations ECLAIRE model comparison Modelling the European Nitrogen budget 16 Ensemble results of the seven regional CTM models are generally better than the individual model results Modelled wet deposition of NOy correlates much better with observed wet deposition than NHx. Regional CTMs are well able to estimate ‘background’ NH 3 concentrations Data from NitroEurope IP is very useful for the ECLAIRE model evaluation! Further analysis of the model-measurement comparison and reasons for inter-model differences is a priority for the next phase in ECLAIRE.

Thank you! ECLAIRE model comparison Modelling the European Nitrogen budget 17

HNO 3 ECLAIRE model comparison Modelling the European Nitrogen budget 18