Evaluation of a regional chemistry transport model using a newly developed regional OMI NO₂ retrieval

Abstract

Abstract. In this paper, we evaluate a high-resolution chemistry transport model (CTM) (3 km x 3 km spatial resolution) with the new Hong Kong (HK) NO2 retrieval developed for the Ozone Monitoring Instrument (OMI) on-board the Aura satellite. The three-dimensional atmospheric chemistry was modelled in the Pearl River Delta (PRD) region in southern China by the Models-3 Community Multiscale Air Quality (CMAQ) modelling system from October 2006 to January 2007. In the HK NO2 retrieval, tropospheric air mass factors (AMF) were recalculated using high-resolution ancillary parameters of surface reflectance, NO2 profile shapes and aerosol profiles of which the latter two were taken from the CMAQ simulation. We also tested four different aerosol parametrizations. Ground level measurements by the PRD Regional Air Quality Monitoring (RAQM) network were used as additional independent measurements. The HK NO2 retrieval increases the NO2 vertical column densities (VCD) by (+31 ± 38) %, when compared to NASA's standard product (SP2), and reduces the mean bias (MB) between satellite and ground measurements by 26 percentage points from −41 to −15 %. The correlation coefficient r is low for both satellite datasets (r = 0.35) due to the high spatial variability of NO2 concentrations. The correlation between CMAQ and the RAQM network is low (r ≈ 0.3) and the model underestimates the NO2 concentrations in the north-western model domain (Foshan and Guangzhou). We compared the CMAQ NO2 time series of the two main plumes with our regional OMI NO2 product. The model overestimates the NO2 VCDs by about 15 % in Hong Kong and Shenzhen, while the correlation coefficient is satisfactory (r = 0.56). In Foshan and Guangzhou, the correlation is low (r = 0.37) and the model underestimates the VCDs strongly (MB = −40 %). In addition, we estimated that the OMI VCDs are also underestimated by about 10 to 20 % in Foshan and Guangzhou because of the influence of the model parameters on the AMF. In this study, we demonstrate that the HK OMI NO2 retrieval reduces the bias of the satellite measurements and thus the dataset can be used to study the magnitude of NO2 concentrations in a regional model. The low bias can be achieved if AMFs are recalculated with more accurate surface reflectance, aerosol profiles and NO2 profiles; only NO2 profiles have been replaced in earlier studies. Since unbiased concentrations are important, for example, in air pollution studies, the results of this paper can be very helpful in future model evaluation studies.