China’s air quality has improved in recent years by the implementation of strict pollution control action plans such as the National “Ten Measures for Air” ratified by the Chinese State Council. To achieve sustained improvements in air quality and targeted pollution control in the coming years the effectiveness of these pollution control initiatives must be scientifically evaluated. Because air quality levels are strongly influenced and at times even dominated by meteorological conditions, a major difficulty of such analysis is quantifying the contributions of meteorological conditions and pollution control initiatives to variations in the respective pollutant concentrations. In this study, we assessed the effectiveness of pollution control efforts for one of the most heavily polluted areas in China—the Beijing-Tianjing-Heibei region—by analyzing (1) the time-frequency properties of the PM2.5 time series collected from 86 monitoring sites in 13 cities of this region during 2013-2018 and (2) the corresponding meteorological conditions retrieved from the reanalysis product of the European Center for Medium-range Weather Forecast (ECMWF). We used the Kolmogorov-Zurbenko filter to separate the original PM2.5 series into three components: Short-term weather-related variations, medium-term seasonal variations, and long-term trends. We constructed regression models to account for the influence of meteorological variables on the PM2.5 concentrations to distinguish their impacts on pollution abatement from those of the emission reduction actions. We found that during 2013-2018, the long-term trends of PM2.5 concentration over 13 cities decreased significantly (22.2%-58.0%), with Xingtai city experiencing the greatest decrease (58.0%). Both meteorological conditions and emission reduction actions contributed to the improvement of air quality, but emission reduction actions were the decisive factor in the significant improvement in air quality. The contributions of meteorological conditions and emission reduction actions were 18.5% and 81.5%, respectively. Among the 13 cities, the meteorological conditions were the most beneficial for Tangshan (29.2%) whereas emission reduction actions played the most important role for Hengshui (92.0%).