In this paper, surface-level ozone in China was estimated by using the source-sink analysis and machine learning model. By analyzing the source and sink of surface ozone, it is clear that ozone mass concentration is influenced by background value, regional and local chemical generation, deposition, chemical removal and Interregional transport comprehensively. Then, the light gradient boosting machine (LGBM) model was used to integrate various corresponding satellite-based variables, numerical model-based meteorological variables and land variables to obtain the high spatial resolution surface mass concentration of ozone in China. Taking June, July, August, 2021 as example, the feasibility of the Tropospheric Monitoring Instrument (TROPOMI) data, the European Centre for Medium-Range Weather Forecasts (ECWMF) data and LGBM model in estimating surface-level ozone mass concentration was analyzed and confirmed.