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Ship emitted NO2 in the Indian Ocean: comparison of model results with satellite data

by K Franke, A Richter, H Bovensmann, V Eyring, P Joeckel, P Hoor, J P Burrows
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The inventory of NOx emission from international shipping has been\nevaluated by comparing NO2 tropospheric columns derived from the\nsatellite instruments SCIAMACHY (January 2003 to February 2008), GOME\n(January 1996 to June 2003), and GOME-2 (March 2007 to February 2008) to\nNO2 columns calculated with the atmospheric chemistry general\ncirculation model ECHAM5/MESSy1 (January 2000 to October 2005). For both\nmeasurements and model consistently the tropospheric excess method was\nused to obtain mean NO2 columns over the shipping lane from India to\nIndonesia, and over two ship free regions, the Bay of Bengal and the\ncentral Indian Ocean. The long-term data set from SCIAMACHY yields the\nfirst monthly analysis of ship induced NO2 enhancements in the Indian\nOcean. Comparison of data from the three instruments and in addition OMI\nreveals differences between the datasets which are discussed with\nrespect to the diurnal cycle of NO2 and the increase in shipping traffic\nover the time period studied.\nIn general, the model simulates the differences between the regions\naffected by ship pollution and ship free regions reasonably well. Minor\ndiscrepancies between model results and satellite data were identified\nduring biomass burning seasons in March to May over India and the\nIndochinese Peninsula and August to October over Indonesia. We conclude\nthat the NOx ship emission inventory used in this study is a good\napproximation of NOx ship emissions in the Indian Ocean for the years\n2002 to 2007. It assumes that around 6 Tg(N) yr(-1) are emitted by\ninternational shipping globally, resulting in 90 Gg(N) yr(-1) in the\nregion of interest when using Automated Mutual Assistance Vessel Rescue\nSystem (AMVER) as spatial proxy. A second model run using lower ship\nemissions estimates of 3-4 Tg(N) yr(-1) globally results in poorer\nagreement with the satellite data.

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