南昌市中心城区绿地景观对PM2.5的影响

随着我国城市化工业化的快速发展,大气环境质量问题越来越受到重视,PM_2.5作为重要的大气污染物,已经引起了公众的普遍关注.城市绿地作为一种半自然的地表景观能在一定程度上影响PM_2.5的浓度与分布,目前的研究主要集中在微观尺度上,在景观尺度上的研究还不多见.本研究采用土地利用回归模型进行监测点加密,基于普通克里格插值法实现PM_2.5浓度的空间分布高精度模拟.然后与通过遥感解译的城市绿地进行耦合,定量分析了城市绿地景观特征、质量等对PM_2.5浓度的影响.结果表明:研究区PM_2.5浓度由市中心向周边不断递减;绿地类型对PM_2.5浓度影响显著;绿地斑块形状对PM_2.5浓度没有显著影响;绿地斑块的面积、质量与PM_2.5浓度呈显著负相关.研究区绿地景观对PM_2.5消减作用距离小于100 m.在消减作用距离内,距离绿地斑块越近,PM_2.5浓度越低.其中,附属绿地和公园绿地对PM_2.5浓度的消减作用距离大于其他绿地类型.

Influence of greenspace landscape pattern on PM2.5 in the center urban area of Nanchang,China

With rapid urbanization and industrialization, more attention has been paid to atmosphere quality in China. PM_2.5, an important atmospheric pollutant, has attracted widespread public attention. Urban greenspace as a semi-natural surface landscape can affect the concentration and distribution of PM_2.5. Current studies mainly focus on micro-scale, with few on landscape scale. In this study, land use regression (LUR) model was used to densify monitoring points. Based on ordinary Kriging interpolation method, the spatial distribution of PM_2.5 concentration was simulated with high precision. We quantitatively analyzed the impacts of urban greenspace landscape characteristics and quality on PM_2.5 concentration by coupling urban greenspace interpreted by remote sensing. The results showed that PM_2.5 concentration decreased from central area to periphery. The impacts of greenspace on PM_2.5 concentration varied with greenspace types. The shape of greenspace had no effect on PM_2.5 concentration, while the area and quality of greenspace were significantly negatively correlated with PM_2.5 concentration. In general, the greenspace had an obvious PM_2.5 reduction effect in the distance of less than 100 m. Within the reduction distance, the closer to the greenspace, the lower the PM_2.5 concentration was. The reduction distance of the affiliated and park greenspace was larger than other greenspace types.