TROPOSPHERIC NO2 COLUMN AND AOD FROM SCIAMACHY: A CASE STUDY ON THE AEROSOL EFFECT ON THE NO2 RETRIEVAL

Andrea Petritoli (1), Elisa Palazzi (1), Giorgio Giovanelli (1), Walter Di Nicolantonio (2), Stefano Scarpanti (2), Alessandra Cacciari (2), Enrico Morisi(2), Simonetta Pagnutti (3), Rodolfo Guzzi (4) (1) Institute of Atmospheric Science and Climate, ISAC- CNR, Bologna, Italy (2) Carlo Gavazzi Space S.p.A. @ Institute of Atmospheric Science and Climate, ISAC- CNR, Bologna, Italy (3) ENEA, Bologna, Italy (4) Agenzia Spaziale Italiana, ASI, Roma, Italy

ABSTRACT

In this work we use Tropospheric Vertical Column Density (TVCD) of NO2 from SCIAMACHY processed at ISAC with the Satellite DOAS Retrieval Processor (SDRP1.0) and simultaneous retrieved Aerosol Optical Properties (AOP) processed at ISAC/CGS by using Aerosol retrieval from SCIAMACHY data Processor (ASP2.2). For selected case studies in the year 2004 the AOP observations will be assimilated in the PROMSAR radiative transfer model to calculate an ad hoc AMF related to each of the SCIAMACHY pixel in the area of interest to improve the accuracy of the NO2 tropospheric column. The method is tested studying the correlation between NO2 TVCD and aerosol where a correlation is expected.

1 INTRODUCTION

Air Mass Factor (AMF) is a key parameter for definition of the accuracy of NO2 measurements obtained from space. Even when considering only clear sky conditions many factors have relevant influence on the AMF calculation and, over large polluted area, the aerosol loading is a leading factor that should be taken into account to improve the accuracy of the TVCD of NO2. For this purpose corresponding and simultaneous retrieval of the tropospheric aerosol optical properties related to the same column is advisable. A sort of assimilation method will be used in this work. The Aerosol Optical Density (AOD) retrieved with ASP2.2 is taken as input for the radiative transfer model to calculate an aerosol corrected AMF and convert NO2 slant column into vertical column. We will focus the data analysis on the Northern India geographical region where also satellite observations have demonstrated the presence of high level of tropospheric NO2 and aerosol and where previous studies reported a correlation between NO2 TVCD and AOD. 1.1 NO2 retrieval Tropospheric NO2 column is retrieved with the SDRP1.0 processor developed at ISAC institute according to the method used first by Richter and Burrows [1] but using a stratospheric back ground to be removed that is latitudinal and longitudinal dependent. This is achieved calculating a stratospheric column that is an average over different supposed no polluted regions (mainly the Atlantic and the Pacific Ocean). The aim is to take in to account also the longitudinal variation of the stratospheric amount that could be relevant and can introduce false pattern in the calculated tropospheric column. Fig. 1 shows an example of the NO2 slant column retrieval from SCIAMACHY observations of 12th of December 2004. In the same figure the respective tropospheric column is plotted using a climatological AMF calculated with the PROMSAR [2] radiative transfer model. Negative values came out from the background removal are set by default to zero. 1.2 AOD retrieval Aerosol optical properties are retrieved by CGS at ISAC using, as input for ASP2.2, calibrated and geolocated SCIAMACHY measurements in nadir mode [3]. In Fig. 2, on the left, the functional diagram of ASP is showed, displaying the main analysis steps contributing to the whole retrieval procedure. Ground-pixels selection is carried out in the pre-processing phase taking into account various geophysical parameters and cloud coverage fraction values, provided by FRESCO algorithm [4], lower than 0.05. Measured spectral reflectances at 364, 387, 429, 683, 754, 775 nm wavelengths are carefully corrected for a systematic underestimation [5,6] as described in this issue by [7]. Aerosol optical parameters are derived by means of Mie theory applied to both standard and in-situ measured microphysical properties. In the right part of Fig. 2, Ångström parameter α[424-754nm] and single scattering albedo ω(500nm) are listed for each aerosol model used in ASP. The global database of monthly Minimum Lambert-Equivalent Reflectivity (MLER) [8] is chosen to estimate the surface contribution to top of the atmosphere (TOA) reflectance. Measured reflectances are fitted with modelled

reflectance spectra by means of the Levenberg-Marquardt least squares method. Modelled spectra are simulated with a radiative transfer code [9] as a function of AOD and a parameter, class, which defines a set of chemico-physical properties pertaining to suspended particles.

Fig. 1. NO2 total slant column observed by SCIAMACHY on 12th of December 2004 retrieved with the SDRP1.0

processor (above). NO2 tropospheric column obtained using a climatological AMF (below).

.

Fig.2. - On the left: Diagram of ASP highligthing the main phases of the aerosol analysis chain; - On the right: Ångström parameter α[424-754nm] and single scattering albedo ω(500nm) for each aerosol class in use in ASP.

Optical Parameters- derived from MIE Theory []-Aerosol Class

(RH) αÅngströmParameter

(424-754 nm)

ω@ 500 nm

Biomass Burning -BB 1.987 0.866

Urban - Ur 1.912 0.917Maritime Lanai - ML 1.32 0.973Rural -Ru(0-50%)

1.1704 0.947

Clean Continental -CC (0-20%) [80%]

1.1503[1.096]

0.951[0.978]

Maritime Polluted -MP(0-50%)

0.7571 0.961

Maritime - Ma(0- 50%) [80%]

0.5187[0.2218]

0.983[0.994]

Desert Background -Ds(0 - 50%)

0.2677 0.901

The couple formed by AOD and class producing the best-fit represents the retrieved aerosol parameters for the spectrum being analysed. A quality check on the analysis is then performed by means of a discrimination index for the best-fitting class comparing it to the other fitting aerosol classes.

2 AMF SENSITIVITY

The influence of the aerosol loading on the retrieved Tropospheric NO2 column is studied through the analysis of AMF sensitivity. The radiative transfer model PROMSAR [2] is used to calculate AMFs under specified atmospheric conditions. PROMSAR is a multiple scattering RTM based on the backward Monte Carlo technique in which variance reducing schemes are used in order to increase computational efficiency [10]. PROMSAR traces the trajectories of individual photons backward through the atmosphere where they are scattered randomly until their statistical weight becomes smaller than a given threshold. What PROMSAR uses to calculate AMFs is the mean path of the photons in the atmosphere layer by layer (averaged on all the photon histories) together with a hypothesis on the vertical profile of the absorber of interest. A series of different RTM simulations have been carried out by varying the type of aerosol (Rural or Urban) and the visibility value which has been estimated from the Koschmieder formula. Visibility is used to define the amount of the aerosol in the atmosphere, here considered in terms of AOD. We see from Fig. 3 that NO2 AMFs decrease with increasing AOD up to 40% values from AOD=0.2 to AOD=1. It can also be noticed the well known dependence of the AMF on the solar zenith angle (SZA). Values for urban aerosol are generally higher than that for rural aerosol.

Fig. 3. On the top: NO2 AMFs computed by PROMSAR model are plotted as a function of AOD (left) and SZA (right) for the Urban aerosol. On the bottom: NO2 AMFs computed by PROMSAR model are plotted as a function

of AOD (left) and SZA (right) for the Rural aerosol. The inverse dependence of AMFs on the AOD values is pointed out.

3 CASE STUDIES

We tested the assimilation with two case studies, 3rd November and 6th November 2004 respectively, over India and in the New Delhi area in particular. The period was chosen accordingly also to the results obtained by [11]. AMF values have been calculated using PROMSAR and taking into account AOD retrieved by ASP. For both days, Fig. 4 shows on the left part the retrieved AOD and the corresponding NO2TVCD are presented in the right part. For these cases we have prepared a look-up table for AMF where its values are calculated according to AOD values and

classes (urban and rural) and NO2TVCD is thus obtained using such aerosol corrected AMF. Correlation between NO2 content and aerosol loading is investigated for each SCIAMACHY pixel related to New Delhi area. Fig. 5 presents the NO2TVCD against corresponding AOD@550 nm. We decide to estimate the correlation between NO2 content and AOD grouping data as a function of the retrieved aerosol class. Anthropogenic aerosols are represented in this analysis by the Urban (Ur) and Biomass Burning (BB) classes. They display an equivalent radiative behaviour. In fact, considering their very similar Ångström parameter values, the multispectral ASP analysis is not able to distinguish these two aerosol classes between each other. On the basis of this remark, in Fig. 5, Ur and BB classes are considered as a whole and present the highest values of R2 (0.81) with respect to the other aerosol classes representative of natural sources (R2 < 0.33). Monkkonen et al. [11] obtained lower correlation coefficients (0.41 at maximum) in the same area but using only ground-observations. The poor statistics we have so far could influence the correlation parameter of course but we also expect possible difference in the scatter plots between ground values and column values. The slope of linear regression for Ur and BB classes is 0.47x10-15(molecxcm-2)-1 and is similar for both days separately. We observed also a great improvement of the correlation coeffient using aerosol corrected NO2TVCD instead of column values obtained with climatological AMF.

Fig. 4. AOD and NO2 tropospheric column over INDIA on November 3rd and 6th 2004.

Fig. 5. AOD vs NO2 column for different aerosol classes for November 3rd and 6th 2004. The correlation coefficients and the respective slopes are reported on the right.

4 CONCLUSIONS In this work we have shown simultaneous observations of TVCD NO2 and AOD from SCIAMACHY retrieved at ISAC-CGS in Bologna. The goal of the work was to show how NO2 retrieval could be improved using the AOD information in the AMF calculation to convert NO2 slant column into vertical. The PROMSAR model is used for this approach and results reported an improvement of the correlation between AOD and NO2 tropospheric column where expected, i.e., in traffic polluted site like that of New Delhi area. 5 ACKNOWLEDGMENTS We are grateful to ESA for providing the SCIAMACHY level 1 data. This work is partly funded by ACCENT-TROPOSAT-2.

6 REFERENCES

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