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The Plain Forestation Project is an important measure designed to alleviate air pollution in Beijing, the capital of China. Ten commonly cultivated forest types of the Plain Forestation Project were studied at three growth stages of leaves. The particulate matter (PM)2.5 concentrations and forest structures were surveyed to analyze the PM2.5 concentration differences between different forest types, and establish a linear relationship between forest structures and PM2.5 concentration differences. The results suggested that forest ecosystems can block and capture PM2.5 from the air. Forests with luxuriant foliage are most effective in removing PM2.5 from the air. The average PM2.5 mass concentration in the Leaf-on Period (LOP) was the lowest when compared with other periods. The PM2.5 concentrations in the forest usually were higher than the control. Correspondingly, PM2.5 concentration indexes were negative values during daytime, but this results were reversed at night. Forests can reduce the diffusion rate of PM2.5 leading to PM2.5 were detained in the forest during daytime, and play an important role in the adsorption or deposition of particulate matter at night. Forest structure was primary reason of the PM2.5 concentration difference between different forests. The PM2.5 concentration index was positively correlated to canopy density, leaf area index (LAI), and mean diameter at breast height (DBH), and negatively correlated to the average tree height (height), forestland area, grass coverage and height

PM2.5 Concentration Differences between Various Forest Types and Its Correlation with Forest Structure