Evaluating the efficacy of air pollution control policies is an essential part of the decision-making process to develop new policies and improve existing measures. In this analysis, we assessed the effects air pollution control policies in the Taiwan Strait Region from 2005 to 2018 using full-coverage, high-resolution PM2.5generated by a satellite-driven machine learning model. A ten-fold cross-validation for our prediction model showed an R2value of 0.89, demonstrating that these predictions can be used for policy evaluation. During the 14-year period, PM2.5levels in all areas of Fujian and Taiwan underwent a significant decrease. Separate regression models for policy evaluation in Taiwan and Fujian showed that all considered policies have mitigated PM2.5pollution to various degrees. The Clean Air Action Plans (CAAP) is the most effective control policy in Taiwan, while the Action Plan of Air Pollution Prevention and Control (APPC-AP) and Three-year Action Plan for Blue Skies (3YAP-BS) as well as their provincial implementation plans are the most successful in Fujian. The effectiveness of control policies, however, varies by land-use types especially for Taiwan.