In this paper, we demonstrated the best fitting window and spectral resolution to retrieve NO2 Vertical Column Density
(VCD) from space borne spectrometer in ultra-violet. The reflectance at TOA was simulated with atmospheric radiation
transfer model SCIATRAN, which takes both molecules absorption and aerosol multiple scattering into consideration.
The NO2 VCD was retrieved using the Differential Optical Absorption Spectroscopy (DOAS) method. There are five
kinds of factors has been taken into the NO2 VCD retrieval sensitivity analysis: fitting window and spectral resolution,
aerosol optical thickness, surface albedo, NO2 concentration in the lower troposphere and sun-satellite geometry. The
results showed that DOAS method cannot well filter the aerosol scattering. High surface reflectivity can strengthen the
signal at TOA and thus enhance the retrieval accuracy. The AMFs become larger dramatically when the sun or satellite
zenith angels are above 70 degree, while the relative azimuth angel affects little in the AMF.
The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.