Abstract:

We analyzed the effect field of green space in Wuhan Zhongshan Park on the air PM10 and PM2.5 concentrations of surrounding built-up environment in four seasons using the LUR model, small-scale measurement, and spatial interpolation technology, aiming to provide scientific basis for the planning and construction of the built-up environment in the surrounding of green space. The results showed that the LUR model for air PM10 and PM2.5 concentrations was successfully developed according to the key variables including geographic variables (the length of traffic road, area of water bodies, area of nonhard underlying surface, distance from the city center, and distance from the edge of green space) and meteorological variables (air temperature, relative humidity, and wind speed), with an adjusted R² of 0.203-0.873 for PM10 and 0.306-0.837 for PM2.5 and a leave-one-out crossvalidation R² of 0.302-0.999 for PM10 and 0.344-0.991 for PM2.5. In addition, the spatial distribution of air PM10 and PM2.5 concentrations was significantly correlated with traffic road length, air temperature, and distance from the city center in the seasonal LUR models (P<0.05). A significant effect of green space on air PM10 and PM2.5 attenuation was detected with an effect field of 250m in winter and 400m in spring, with the maximum of daily reduction of 47.2 μg·m^-3 for air PM₁₀ and 15.5 μg·m^-3 for air PM_2.5. The highest air PM₁₀ and PM_2.5 concentration occurred at 8:00-9:00 in spring, summer, and autumn, and at 15:00-16:00 in winter.

Key words: urban green space, air PM₁₀, air PM_2.5, land use regression model (LUR), effect field.