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Carbon monoxide spatial gradients over source regions as observed by SCIAMACHY: A case study for the United Kingdom
Authors:Iryna Khlystova  Michael Buchwitz  John P Burrows  Heinrich Bovensmann  David Fowler
Institution:1. Institute of Environmental Physics (IUP), University of Bremen FB1, P.O. Box 330440, Otto Hahn Allee 1, 28334 Bremen, Germany;2. Centre for Ecology and Hydrology (CEH), Bush Estate Penicuik, Midlothian EH26 0QB, United Kingdom
Abstract:Carbon monoxide (CO) is an important air pollutant whose emissions and atmospheric concentrations need to be monitored. The measurements of the SCIAMACHY instrument on ENVISAT are sensitive to CO concentration changes at all atmospheric altitude levels including the boundary layer. The SCIAMACHY CO measurements therefore contain information on CO emissions. Until now no studies have been published where the SCIAMACHY CO measurements have been used to quantify CO emissions by applying, for example, inverse modelling approaches. Here we report about a step in this direction. We have analysed three years of CO columns to investigate if spatial gradients resulting from United Kingdom (UK) CO emissions can be observed from space. The UK is an interesting target area because the UK is a relatively well isolated CO source region. On the other hand, the UK is not the easiest target as its emissions are only moderate and because the surrounding water has low reflectivity in the 2.3 μm spectral region used for CO retrieval. We determined horizontal CO gradients from seasonally and yearly averaged CO during 2003–2005 over the UK taking into account daily wind fields. We show that the measured CO longitudinal (downwind) gradients have the expected order of magnitude. The estimated 2σ error of the gradients depends on time period and applied filtering criteria (e.g., land only, cloud free) and is typically 10–20% of the total column. The gradients are barely statistically significant within the 2σ error margin. This is mainly because of the relatively high noise of the SCIAMACHY CO measurements in combination with a quite low number of measurements (∼100) mainly due to cloud cover.
Keywords:Satellite remote sensing  Tropospheric composition  Air pollution
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