NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

Abstract

Abstract. We present a new numerical code, Mexican Maxdoas Fit (MMF), developed to retrieve profiles of different trace gases from the network of MAX-DOAS instruments operated in Mexico City. MMF uses differential slant column densities (dSCDs) retrieved with the QDOAS (Danckaert et al., 2013) software. The retrieval is comprised of two steps, an aerosol retrieval and the trace gas retrieval that uses the retrieved aerosol profile in the forward model for the trace gas. For forward model simulations, VLIDORT is used (e.g. Spurr et al., 2001; Spurr, 2006, 2013). Both steps use constrained least square fitting, but the aerosol retrieval uses Tikhonov regularization and the trace gas retrieval optimal estimation. Aerosol optical depth and scattering properties from the AERONET database, averaged ceilometer data, WRF-Chem model data as well as temperature and pressure sounding data are used for different steps in the retrieval chain. The MMF code was applied to retrieve NO2 profiles with two degrees of freedom (DOFs = 2) from spectra of the MAX-DOAS instrument located at the UNAM campus. We describe the full error analysis of the retrievals and include a sensitivity exercise to quantify the contribution of the uncertainties in the aerosol extinction profiles to the total error. A dataset comprised of measurements from January 2015 to July 2016 was processed and the results compared to independent surface measurements. We concentrate on the analysis of 4 single days and additionally present diurnal and annual variabilities from averaging the 1.5 years of data. Even though the total error is considerably large (depending on the exact counting 14–20 %) this work still provides new and relevant information about NO2 in the boundary layer of Mexico City.

Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies using synthetic data

“…The Heidelberg Profile Retrieval Algorithm (HEIPRO) is an updated version of the algorithm already described in detail in Frieß et al (2006Frieß et al ( , 2011. It uses the SCIATRAN radiative transfer model version 2.1.5 (Rozanov et al, 2014) in discrete ordinate mode with full multiple-scattering, full spherical geometry for single-scattering and plane-parallel geometry for multiple-scattering light.…”

“…Testing the performance of algorithms for the retrieval of the atmospheric state using remote-sensing measurements on the basis of synthetic data is a method that has been widely used in the scientific community. In particular, numerous synthetic studies that investigated the performance of MAX-DOAS retrieval algorithms were published in the past (Wagner et al, 2004;Frieß et al, 2006;Hay, 2010;Vlemmix et al, 2011;Yilmaz, 2012;Hartl and Wenig, 2013;Holla, 2013;Zielcke, 2015). This paper presents the first intercomparison of eight state-of-the-art algorithms for the retrieval of vertical profiles of aerosols and trace gases using synthetic MAX-DOAS measurements.…”

Enhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic data

“…It can be determined by Mie calculations and ranges between 0.5 and 3 for typical atmospheric aerosol in the UV-Vis spectral range. As is the case with earlier OEM retrieval algorithms (Yilmaz, 2012;Friedrich et al, 2019;Wang et al, 2013), RAPSODI can transform individual state vector elements to numerically more favourable quantities x before the OEM formalism is applied (in Figure 1, these transformations are indicated by "t()"). In this work, we make use of two kinds of transformations: (1) the "log"-transformation allowing us to retrieve parameters in logarithmic space, hence x = ln(x).…”