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The growth of mega-cities leads to air quality problems directly affectingthe citizens. Satellite measurements are becoming of higher quality andquantity, which leads to more accurate satellite retrievals of enhancedair pollutant concentrations over large cities. In this paper, we compare anddiscuss both an existing and a new method for estimating urban-scale trendsin CO emissions using multi-year retrievals from the MOPITT satelliteinstrument. The first method is mainly based on satellite data, and has theadvantage of fewer assumptions, but also comes with uncertainties andlimitations as shown in this paper. To improve the reliability of urban-to-regional scale emission trend estimation, we simulate MOPITT retrievals usingthe Weather Research and Forecast model with chemistry core (WRF-Chem). Thedifference between model and retrieval is used to optimize CO emissions inWRF-Chem, focusing on the city of Madrid, Spain. This method has theadvantage over the existing method in that it allows both a trend analysis ofCO concentrations and a quantification of CO emissions. Our analysis confirmsthat MOPITT is capable of detecting CO enhancements over Madrid, althoughsignificant differences remain between the yearly averaged model output andsatellite measurements (<i>R</i><sup>2</sup> =  0.75) over the city. After optimization, wefind Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006compared with the EdgarV4.2 emission inventory. The MOPITT-derived emissionadjustments lead to better agreement with the European emission inventoryTNO-MAC-III for both years. This suggests that the downward trend in COemissions over Madrid is overestimated in EdgarV4.2 and more realisticallyrepresented in TNO-MACC-III. However, our satellite and model based emissionestimates have large uncertainties, around 20 % for 2002 and 50 % for 2006

Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations