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Inverse Modeling of European Ch4 Emissions: Sensitivity to the Observational Network : Volume 9, Issue 5 (06/10/2009)

By Villani, M. G.

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Book Id: WPLBN0003981575
Format Type: PDF Article :
File Size: Pages 38
Reproduction Date: 2015

Title: Inverse Modeling of European Ch4 Emissions: Sensitivity to the Observational Network : Volume 9, Issue 5 (06/10/2009)  
Author: Villani, M. G.
Volume: Vol. 9, Issue 5
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2009
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Bergamaschi, P., Meirink, J. F., Krol, M., Villani, M. G., & Dentener, F. (2009). Inverse Modeling of European Ch4 Emissions: Sensitivity to the Observational Network : Volume 9, Issue 5 (06/10/2009). Retrieved from http://www.ebooklibrary.org/


Description
Description: European Commission, Joint Research Centre, Institute for Environment and Sustainability, 21027 Ispra (VA), Italy. Inverse modeling is widely employed to provide top-down emission estimates using atmospheric measurements. Here, we analyze the dependence of derived CH4 emissions on the sampling frequency and density of the observational surface network, using the TM5-4DVAR inverse modeling system and synthetic observations. This sensitivity study focuses on Europe.

The synthetic observations are created by TM5 forward model simulations. The inversions of these synthetic observations are performed using virtually no knowledge on the a priori spatial and temporal distribution of emissions, i.e. the emissions are derived mainly from the atmospheric signal detected by the measurement network.

Using the European network of stations for which continuous or weekly flask measurements are available for 2001, the synthetic experiments can retrieve the true annual total emissions for single countries such as France within 20%, and for all North West European countries together within ~5%. However, larger deviations are obtained for South and East European countries due to the scarcity of stations in the measurement network. Upgrading flask sites to stations with continuous measurements leads to an improvement for central Europe in emission estimates. For realistic emission estimates over the whole European domain, however, a major extension of the number of stations in the existing network is required. We demonstrate the potential of an extended network of a total of ~60 European stations to provide realistic emission estimates over the whole European domain.


Summary
Inverse modeling of European CH4 emissions: sensitivity to the observational network

Excerpt
Bergamaschi, P., Krol, M., Dentener, F., Vermeulen, A., Meinhardt, F., Graul, R., Ramonet, M., Peters, W., and Dlugokencky, E. J.: Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5, Atmos. Chem. Phys., 5, 2431–2460, 2005.; Bergamaschi, P. (Ed.): Atmospheric Monitoring and Inverse Modelling for Verification of National and EU Bottom-up GHG Inventories – report of the workshop Atmospheric Monitoring and Inverse Modelling for Verification of National and EU Bottom-up GHG Inventories under the mandate of Climate Change Committee Working Group I, Casa Don Guanella, Ispra, Italy (8–9 March 2007), European Commission Joint Research Centre, Institute for Environment and Sustainability, 153 pp., 2007a.; Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Dentener, F., Wagner, T., Platt, U., Kaplan, J. O., Körner, S., Heimann, M., Dlugokencky, E. J., and Goede, A.: Satellite chartography of atmospheric methane from SCIAMACHY onboard ENVISAT: (II) Evaluation based on inverse model simulations, J. Geophys. Res., $112$, D02304, doi:02310.01029/02006JD007268, 2007b.; Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Villani, M. G., Houweling, S., Dentener, F., Dlugokencky, E. J., Miller, J. B., Engel, A., and Levin, I.: Inverse Modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res.-Atmos., accepted, 2009.; Bousquet, P., Hauglustaine, D. A., Peylin, P., Carouge, C., and Ciais, P.: Two decades of OH variability as inferred by an inversion of atmospheric transport and chemistry of methyl chloroform, Atmos. Chem. Phys., 5, 2635–2656, 2005.; Brühl, C. and P. J. Crutzen: The MPIC 2D model, in NASA Ref. Publ. 1292, vol. 1, 103–104, 1993.; Carouge, C., Bousquet, P., Peylin, P., Rayner, P. J., and Ciais, P.: What can we learn from European continuous atmospheric CO2 measurements to quantify regional fluxes – Part 1: Potential of the network, Atmos. Chem. Phys. Discuss., 8, 18591–18620, 2008a.; Carouge, C., Peylin, P., Rayner, P. J., Bousquet, P., Chevallier, F., and Ciais, P.: What can we learn from European continuous atmospheric CO2 measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup, Atmos. Chem. Phys. Discuss., 8, 18621–18649, 2008b.; Chen, Y.-H. and Prinn, R. G.: Estimation of atmospheric methane emissions between 1996 and 2001 using a three-dimensional global chemical transport model, J. Geophys. Res., $111$, D10307, doi:10310.11029/12005JD006058, 2006.; Chevallier, F.: Impact of correlated observation errors on inverted CO2 surface fluxes from OCO measurements, Geophys. Res. Lett., $34$, L24804, doi:10.1029/2007GL030463, 2007.; Dlugokencky, E. J., Masaire, K. A., Lang, P. M., Steele, P. P., and Nisbet, E. G.: A dramatic decrease in the growth rate of atmospheric methane in the northern hemisphere during 1992, Geophys. Res. Lett., $21$, 45–48, 1994.; Dlugokencky, E. J., Houweling, S., Bruhwiler, L., Masarie, K. A., Lang, P. M., Miller, J. B., and Tans, P. P.: Atmospheric methane levels off: Temporary pause or a new steady-state?, Geophys. Res. Lett., $30$(19), 1992, doi:1910.1029/2003GL018126, 2003.; Frankenberg, C., Bergamaschi, P., Butz, A., Houweling, S., Meirink, J. F., Notholt, J., Petersen, A. K., Schrijver, H., Warneke, T., and Aben, I.: Tropical methane emissions: A revised view from SCIAMACHY onboard ENVISAT, Geophys. Res. Lett., $35$, L15811, doi:10.1029/2008GL034300, 2008.; Hein, R., Crutzen, P. J., and Heimann, M.: An inverse modeling approach to investigate the global atmospheric methane cycle, Global Biogeochem. Cy., $11$, 43–76, 1997.; Houweling, S., Dentener, F., and Lelieveld, J.: The impact of nonmethane hydrocarbon compounds on tropospheric photochemistry, J. Geophys. Res., $103$(D9), 10673–10696, 1988.; Houweling, S., Kaminski, T., Dentener, F., Lelieveld, J., and Heimann, M.: Inverse modeling

 

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