北京市中心城区绿地空间布局与PM<subscript>2.5</subscript> 的关联性研究. (Chinese)

PM 2.5 作为我国大气环境的主要污染物之一,对社会经济和公众健康都有较大的危害。绿 地通过干沉积、降低环境温度等途径具有降减PM 2.5 浓度的作用。基于2021 年北京中心城区监测 站点PM 2.5 数据和高清影像,借助反距离加权插值、监督分类、景观指数、相关性分析,探究PM 2.5 和 绿地的空间分布规律及两者的内在关联。结果表明:PM 2.5 年均值呈现北部、西南部低,中部和东部 高的空间特征;绿地总体呈现由外环向内环逐渐减少的空间特征;城区绿地空间布局对PM 2.5 浓度 有显著影响,尤其表现在春秋两季;SPLIT、LPI 是影响PM 2.5 最重要的景观指数;PLAND、COHEION、 LPI 与PM 2.5 浓度呈显著负相关,而SPLIT 与PM 2.5 浓度呈正相关;LSI 与PM 2.5 浓度无显著相关。研 究结果可为绿地空间优化及PM 2.5 污染防治提供依据. PM2郾5, as one of the major pollutants in China蒺s atmospheric environment, poses a greater risk to both socio-economic and public health. Based on PM2郾5 data and high-definition images from monitoring stations in central Beijing in 2021, the spatial distribution pattern of PM 2.5 and green areas and their intrinsic correlation were explored with the help of inverse distance interpolation, supervised classification, landscape index and correlation analysis. The results show that: annual average PM 2.5 values show a spatial pattern of low values in the north and south-west and high values in the centre and east. The overall spatial characteristics of the green space show a gradual decrease from the outer ring to the inner ring. The spatial layout of urban green spaces has a significant influence on PM 2.5 concentration, especially in spring and autumn; SPLIT, LPI are the most important landscape indices affecting PM 2.5 ; PLAND, COHEION and LPI have a significant negative relationship with PM 2.5 concentration, while SPLIT has a positive relationship with PM 2.5 concentration; LSI has no significant correlation with PM 2.5 concentration. The results of the study can provide a basis for green space optimization and PM 2.5 pollution prevention and control. [ABSTRACT FROM AUTHOR]

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