Ambient SO pollution poses a great threat on air quality, human health, and ecosystem safety. The ground-level SO monitoring sites over China have been established during the past years, while the long-term SO data was still missing before 2014, which cannot reveal the evolution trend of SO pollution and assess its response to the anthropogenic activity. In this work, we developed a high-quality random forest (RF) model to simulate the long-term SO concentration across the entire China from 1973 to 2014, based on substantial explanatory variables (e.g., meteorological factors, SO emission intensity, land use types). The 10-fold cross-validation R value and root mean square error (RMSE) over China reached 0.64 and 17.06 μg/m, respectively, both of which were significantly higher than those of other models such as back propagation neural network (BPNN) and generalized regression neutral network (GRNN). Among all of the predictors, T displayed the highest relative importance value, followed by WS, Prec, SO emission intensity, RH, DOY, elevation, and the lower one for land use types and P. The estimated mean SO concentration during 1973-2014 displayed the remarkably spatial variation with the higher value in North China Plain (NCP) and Middle part of Inner Mongolia. This historical SO level estimation suggested that air pollution was not a new environmental issue that could be dated back to 1973. Overall, the annually mean SO level for each grid increased from 29.46 ± 9.79 to 31.44 ± 8.77 μg/m from 1973 to 2014. The annually mean SO concentration in NCP showed rapid increase from 34.32 ± 3.05 to 36.97 ± 3.18 μg/m during 1973-2002, whereas they decreased significantly after 2003 (from 37.46 ± 3.20 to 36.13 ± 3.48 μg/m during 2003-2014). The gradual decrease since 2003 was benefitted from the adjustment of the energy consumption structure and the adoption of emission control technologies. However, the SO levels in some western regions showed the violent increases since 2003 due to the proposal of "development of the western region". The estimated daily SO concentration across the entire China could provide the essential data for epidemiological research and air pollution prevention.