Abstract. Satellite observations of the tropospheric NO₂ vertical column density (VCD) are closely correlated to, and thus can be used to estimate, surface NO_x emissions. In this study, the NO₂ VCD simulated by a regional chemical transport model with emissions data from the updated Regional Emission inventory in ASia (REAS) version 2.1 were validated through comparison with multisatellite observations during the period 2000–2010. Rapid growth in NO₂ VCD (~11% year⁻¹) driven by the expansion of anthropogenic NO_x emissions was identified above the central eastern China (CEC) region, except for the period during the economic downturn. In contrast, slightly decreasing trends (~2% year⁻¹) were identified above Japan accompanied by a decline in anthropogenic emissions. To systematically compare the modeled NO₂ VCD, we estimated sampling bias and the effect of applying the averaging kernel information, with particular focus on the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. Using the updated REAS, the modeled NO₂ VCD reasonably reproduced annual trends observed by multisatellites, suggesting that the rate of increase of NO_x emissions estimated by the updated REAS inventory would be robust. Province-scale revision of emissions above CEC is needed to further refine emission inventories. Based on the close linear relationship between modeled and observed NO₂ VCD and anthropogenic NO_x emissions, NO_x emissions in 2009 and 2010, which were not covered by the updated REAS inventory, were estimated. NO_x emissions from anthropogenic sources in China in 2009 and 2010 were determined to be 26.4 and 28.5 Tg year⁻¹, respectively, indicating that NO_x emissions increased more than twofold between 2000 and 2010. This increase reflected the strong growth of anthropogenic emissions in China following the rapid recovery from the economic downturn from late 2008 until mid-2009. Our method consists of simple estimations from satellite observations and provides results that are consistent with the most recent inventory of emissions data for China.