The impact of urban green space landscape on PM2.5 in the central urban area of Nanchang city, China

With China's rapid urbanization and industrialization, PM2.5 as a significant air pollutant, has drawn considerable public attention and strengthen the public's awareness of air quality. As a semi-natural landscape, many studies indicated that urban green space could influence the concentration and distribution of PM2.5 to a certain extent. However, most current researches were conducted at population or community scale, and how the urban green space affects PM2.5 at landscape scale was seldom studied. Taking the central urban area of Nanchang city, China, as a case, this study firstly encrypted the monitoring points by the land use regression model (LUR), and simulated the spatial distribution of PM2.5 concentration with high-precision based on the ordinary kriging interpolation method. Then, based on the urban green space data interpreted by remote sensing, the influence of urban green space landscape characteristics on PM2.5 concentration was quantitatively analyzed. The results showed that: (1) The PM2.5 concentration in the study area decreases continuously from the city center to the periphery; (2) Landscape pattern of green space has a significant effect on PM2.5 concentration. Patch green space has a stronger effects on PM2.5 concentrations than corridor green space did; (3) The attributes of area and NDVI of green space have a significant negative correlation with PM2.5 concentration. (4) The effective distance that green space can affect PM2.5 in the study area was less than 100 m. This study is expected to provide some references for lightning PM2.5 pollution by means of optimization of urban green space.