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Exploring the Sensitivity of the OMI ‐ NO 2 Product to emission Changes Across Europe using a Chemistry Transport Model M. Schaap, L. Curier, R. Kranenburg,

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Presentation on theme: "Exploring the Sensitivity of the OMI ‐ NO 2 Product to emission Changes Across Europe using a Chemistry Transport Model M. Schaap, L. Curier, R. Kranenburg,"— Presentation transcript:

1 Exploring the Sensitivity of the OMI ‐ NO 2 Product to emission Changes Across Europe using a Chemistry Transport Model M. Schaap, L. Curier, R. Kranenburg, F. Boersma, H. Eskes, A. Segers, R. Timmermans

2 Introduction In Europe, official emissions are reported are reported to EEA and UNECE/EMEP. Although many countries report high quality data, a number of caveats exist: the inventory methodologies vary from nation to nation data gaps exist not real-time discrepancies between eastern and western Europe M. Schaap Fossil Fuel pilot Officially reported emissions (Gg) for year: 2000 Reported in + 45% Nox Germany PM10

3 Goals To contribute to the verification and improvement of the European emission inventory by synergistic use of satellite data and a chemistry transport model. To inform you on activities performed at TNO with OMI-NO 2 data M. Schaap Fossil Fuel pilot

4 Chemistry transport model LOTOS-EUROS Lower troposphere up to 3.5 Km CBM-IV chemistry Explicit N 2 O 5 hydrolysis ISORROPIA-II equilibrium mod. NO 2 columns calculated using OMI averaging kernels EnKF data assimilation Participated in most model comparisons (GLOREAM, EURODELTA, AQMEII) Member of MACC ensemble Labelling module that tracks source contributions for all N- containing compounds See Kranenburg et al., 2013 M. Schaap Fossil Fuel pilot

5 Emissions Labels 2005: MACC-2005 database 2020: MACC-2005 scaled by GAINS 2020 totals per sector Temporal profiles per sector SNAP sectors 1Energy industries 3Industrial combustion 7Road transport 8Non-road transport 9Agriculture Other Label definition: -6 source sectors -5 hours of the day between 9 and 14 -Boundary conditions M. Schaap Fossil Fuel pilot

6 Annual mean modelled and retrieved NO 2 distribution M. Schaap Fossil Fuel pilot ModelOMI Systematic bias of 1.10 15 molec/cm 2 Spatial correlation R 2 = 0.91

7 Comparison over Europe Eastern Europe Western EuropeIberian Peninsula 2007 Netherlands M. Schaap Fossil Fuel pilot

8 Power generation Sector contributions to NO 2 columns at OMI overpass M. Schaap Fossil Fuel pilot

9 Off Road transport Sector contributions NO 2 columns at OMI overpass M. Schaap Fossil Fuel pilot

10 Road transport Sector contributions to NO 2 columns at OMI overpass M. Schaap Fossil Fuel pilot

11 Approach: M. Schaap Fossil Fuel pilot Seasonal component Annual trends [Weatherhead et al 1998] LOTOS-EUROS simulation with constant 2005 emissions Match to OMI columns using averaging kernel Trend estimate in the bias between OMI and LOTOS-EUROS

12 Satellite derived trends in OMI-NO 2 v1 NO2 trends show decreasing values of 3-6 % a year between 2005 and 2010. Data often used as a first order estimate of the NO x emission trend Comparison to 2011 reporting for 2009 M. Schaap Fossil Fuel pilot

13 Impact of emission scenario on NO 2 columns M. Schaap Fossil Fuel pilot Emissions NO2 Columns

14 M. Schaap Fossil Fuel pilot Island states Coastal countries Large countries Sea areas

15 Extension to 2012 using OMI-v2 and full data assimilation Assimilation indicated a very slow decline until 2012, if any! Reason: V2.0 contains much smaller trends! M. Schaap Fossil Fuel pilot Parameter estimate using v2 Trend analysis on v1 % change over 5 years

16 Comparison v1 and v2 for 2005-2010 M. Schaap Fossil Fuel pilot

17 Meteo corrected All data

18 M. Schaap Fossil Fuel pilot Change of Annual emissions and levels normalized to 2005

19 Impact of direct NO2 percentage diesel cars from 3 to 20% M. Schaap Fossil Fuel pilot NO2 evaluation for 1990-2009 %

20 Conclusions  We have developed a source apportionment tool to investigate emission sector contributions to satellite products.  Source sector contributions show distinctly different spatial patterns.  For land locked and large countries OMI-NO2 trends can be translated into emission changes.  Both in-situ and remote sensed NO2 levels show lower downward trends than reported emissions.  Improvements possible through update temporal variability of emissions, natural emissions, extension of vertical extend LE.  This study highlights the need for a combined use of models, a-priori emission estimates and satellite data to verify emission trends. M. Schaap Fossil Fuel pilot

21 Thank you for you attention Reference: Schaap et al., Remote Sens., 5(9), 4187-4208; Curier et al., 2014 Acknowledgement: We acknowledge the support of ESA project GlobEmission and the EC-FP7 ENERGEO project Monday, April 11, 2011 R. Lyana Curier 21 M. Schaap Fossil Fuel pilot

22 Comparison to AIRBASE ground level NO 2 M. Schaap Fossil Fuel pilot

23 Contribution of the emissions between 09-14 to NO 2 columns at OMI overpass M. Schaap Fossil Fuel pilot

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