Abstract
Abstract. In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF ≤ 0.3 and CF ≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity ( ∼ 0.98) and the mean satellite underestimation is reduced to about half (from ∼ 7 to ∼ 3.5 × 1015 molecules cm−2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤ 50 km) to 0.953 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km).
Highlights
Nitrogen dioxide (NO2) is an important trace gas in the atmosphere
Tropospheric NO2 vertical column density (VCD) measurements performed with the MAX-DOAS system of Aristotle University of Thessaloniki (AUTH) in Guangzhou, China, are presented and used for comparisons with relevant satellite products
The MAX-DOAS data are compared with corresponding Ozone Monitoring Instrument (OMI)/Aura, GOME-2/MetOp-A and GOME2/MetOp-B overpass data, revealing good correlation coefficients, i.e., 0.996, 0.882, 0.795, respectively, and slope values ranging between 0.83 and 0.98
Summary
Nitrogen dioxide (NO2) is an important trace gas in the atmosphere. It plays a critical role in the tropospheric photochemistry (Seinfeld and Pandis, 1998; Finlayson-Pitts and Pitts, 2000) and contributes to the radiative forcing of the atmosphere (Solomon et al, 1999). NO2 is an important trace gas in the troposphere in Chinese megacities (Richter et al, 2005; Ma et al, 2013; Jin et al, 2016) and there is significant evidence that secondary aerosols formed from NOx, as well as SO2 and volatile organic compounds, contribute to haze pollution events which are frequently observed over urban agglomerations in China (Fu et al, 2014; Jiang et al, 2015; Huang et al, 2014). Several studies have validated satellite NO2 products over North China and the Yangtze River Delta region using ground-based observations (e.g., Ma et al, 2013; Chan et al, 2015; Jin et al, 2016; Wang et al, 2017b) or have used the satellite measurements of NO2 to estimate NOx emissions (e.g., Ding et al, 2015; Han et al, 2015). The tropospheric NO2 vertical column densities derived by the MAX-DOAS are presented and compared with tropospheric NO2 retrievals from OMI/Aura, GOME-2/MetOp-A and GOME-2/MetOp-B satellites
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