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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 one 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 0.76 for GOME-2B and 0.99 for GOME-2A. 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 0.99 from about 0.6, the slope value is almost doubled (~ 0.8) and the mean satellite underestimation is reduced to about half (from ~ 7 to ~ 3.5 × 1015 molecules/cm2). 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 0.76 (d ≤ 50 km) to 0.93 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km). [ABSTRACT FROM AUTHOR]