Megacities are immense sources of air pollutants, with large impacts on air quality and climate. However, emission inventories in many of them still are highly uncertain, particularly in developing countries. Satellite observations allow top-down estimates of emissions to be made for nitrogen oxides (NO(x) = NO + NO(2)), but require poorly quantified a priori information on the NO(x) lifetime. We present a method for the simultaneous determination of megacity NO(x) emissions and lifetimes from satellite measurements by analyzing the downwind patterns of NO(2) separately for different wind conditions. Daytime lifetimes are ~4 hours at low and mid-latitudes, but ~8 hours in wintertime for Moscow. The derived NO(x) emissions are generally in good agreement with existing emission inventories, but are higher by a factor of 3 for the Saudi Arabian capital Riyadh.

[1] We extend the analysis of a global CH 4 data set retrieved from SCIAMACHY (Frankenberg et al., 2006) by making a detailed comparison with inverse TM5 model simulations for 2003 that are optimized versus high accuracy CH 4 surface measurements from the NOAA ESRL network. The comparison of column averaged mixing ratios over remote continental and oceanic regions shows that major features of the atmospheric CH 4 distribution are consistent between SCIAMACHY observations and model simulations. However, the analysis suggests that SCIAMACHY CH 4 retrievals may have some bias that depends on latitude and season (up to $30 ppb). Large enhancements of column averaged CH 4 mixing ratios ($50-100 ppb) are observed and modeled over India, Southeast Asia, and the tropical regions of South America, and Africa. We present a detailed comparison of observed spatial patterns and their seasonal evolution with TM5 1°Â 1°zoom simulations over these regions. Application of a new wetland inventory leads to a significant improvement in the agreement between SCIAMACHY retrievals and model simulations over the Amazon basin during the first half of the year. Furthermore, we present an initial coupled inversion that simultaneously uses the surface and satellite observations and that allows the inverse system to compensate for the potential systematic bias. The results suggest significantly greater tropical emissions compared to either the a priori estimates or the inversion based on the surface measurements only. Emissions from rice paddies in India and Southeast Asia are relatively well constrained by the SCIAMACHY data and are slightly reduced by the inversion.

Our iterative maximum a posteriori (IMAP) DOAS algorithm (12) is based on optimal estimation (S1,S2) and uses the depth of the absorption structures of the respective

[1] A new retrieval algorithm for the determination of aerosol properties using MultiAXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements based on nonlinear optimal estimation is presented. Using simulated MAX-DOAS measurements of the optical depth of the collision complex of oxygen (O 4 ) as well as the variation of the intensity of diffuse skylight measured at different viewing directions and wavelengths, the capability of this measurement technique to derive the aerosol extinction profile as well as information on the phase function and single scattering albedo is demonstrated. The information content, vertical resolution and retrieval errors under various atmospheric conditions are discussed. Furthermore, it is demonstrated that the assumption of a smooth variation of the aerosol properties between successive measurements can be used to improve the quality of the retrieval by applying a Kalman smoother. The results of these model studies suggest that the achievable precision of MAX-DOAS measurements of the aerosol total optical depth is better than 0.01 and thus comparable with established methods of aerosol detection by Sun photometers (e.g., within the AERONET network) over a wide range of atmospheric conditions. Moreover, MAX-DOAS measurements contain information on the vertical profile of the aerosol extinction, and can be performed with relatively simple, robust and self-calibrating instruments.

[1] Multi AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of the oxygen dimer O 4 which can serve as a new method for the determination of atmospheric aerosol properties are presented. Like established methods, e.g., Sun radiometer and LIDAR measurements, MAX-DOAS O 4 observations determine optical properties of aerosol under atmospheric conditions (not dried). However, the novel technique has two major advantages: It utilizes differential O 4 absorption structures and thus does not require absolute radiometric calibration. In addition, O 4 observations using this method provide a new kind of information: since the atmospheric O 4 profile depends strongly on altitude, they can yield information on the atmospheric light path distribution and in particular on the atmospheric aerosol profile. From O 4 observations during clear days and from atmospheric radiative transfer modeling, we conclude that our new method is especially sensitive to the aerosol extinction close to the ground. In addition, O 4 observations using this method yield information on the penetration depth of the incident direct solar radiation. O 4 observations at different azimuth angles can also provide information on the aerosol scattering phase function. We found that MAX-DOAS O 4 observations are a very sensitive method: even aerosol extinction below 0.001 could be detected. In addition to the O 4 absorptions we also investigated the magnitude of the Ring effect and the (relative) intensity. Both quantities yield valuable further information on atmospheric aerosols. From the simultaneous analysis of the observed O 4 absorption and the measured intensity, in particular, information on the absorbing properties of the aerosols might be derived. The aerosol information derived from MAX-DOAS observations can be used for the quantitative analysis of various trace gases also analyzed from the measured spectra.