GIS-Based Urban Afforestation Spatial Patterns and a Strategy for PM2.5 Removal

Within the scope of ecological development planning in China, afforestation is highly valued. However, the scientific planning of afforestation still has inadequacies. There are few studies on the spatial distribution of urban forests targeted at air quality improvement. Here, we implemented a virtual experiment to evaluate whether different tree planting distribution plans with the same afforestation scale would have a significant effect on fine particulate matter (PM2.5) removal. As a case study of Wuhan, this paper identified the statistical regularity between PM2.5 concentration and adsorption of representative trees through field sampling and measurement, simulated the influence of different afforestation plans on PM2.5 concentration based on Geographic Information System (GIS), judged the significance of the difference of the plans, and proposed a greening distribution strategy. The results show that different forest layouts had no significant impact on PM2.5 in the administrative region, and the concentration reduction rate was only 1%–2%. Targeted planting of trees in heavily polluted areas in the city center would have achieved better air quality improvement, with a reduction rate of 3%–5%. In Wuhan construction areas, trees should be planted to increase the forest coverage rate to 30%. The edge of the urban metropolitan development zone needs to be strengthened with trees to form a forest belt 10 km–20 km wide, with a forest coverage rate of at least 60%. In general, the capability of trees to reduce PM2.5 concentration is weak. The fundamental way to improve air quality is to reduce emissions; planting trees is only an auxiliary measure. More ecological forest functions should be considered in city-wide afforestation distribution.