城市绿地景观格局对PM2.5、PM10分布的影响及尺度效应

Influence of Urban Green Landscape Pattern on the Concentration of PM_(2.5)/PM_(10) and Scale Effect in Zhengzhou, China

基于2015—2016年郑州市9个国控监测站点的连续监测数据及遥感影像数据,在1~6km尺度上分析PM_(2.5)、PM_(10)与城市绿地景观格局各季节的耦合机制及尺度效应。结果表明:在春季3km×3km^6km×6km尺度,夏季3km×3km、5km×5km、6km×6km尺度,秋季2km×2km^6km×6km尺度增加绿地面积对PM_(10)浓度具有显著缓解效应,且在秋季5km×5km尺度缓解作用最佳;当绿地面积在春、冬季达到3km×3km,秋季达到5km×5km尺度以上时,绿地面积的增加才能使PM_(2.5)浓度降低。在秋季2km×2km^6km×6km尺度加强大型绿地斑块的保护及拓展、提高绿地斑块集群效应可以显著降低PM_(10)浓度,尤其在3km×3km尺度减缓作用最佳;分别在冬季4km×4km、5km×5km尺度增加大型斑块面积、提高斑块聚集程度能明显缓解PM_(2.5)浓度。在冬季1km×1km尺度或春季1km×1km尺度提高绿地斑块形状复杂程度可以分别降低PM_(10)和PM_(2.5)浓度。该成果可以为多尺度城市绿地系统规划设计提供定量依据。

The coupling mechanism and scale effect between the concentration of PM2.5/PM10 and urban green landscape pattern on 1km to 6km scale were analyzed based on the meteorological data and remote sensing image data from 9 monitoring stations of Zhengzhou city from 2015 to 2016.The results indicated that increasing green land area significantly reduced the PM10 concentration in 3km×3km to 6km×6km scale in spring,3km×3km,5km×5km,6km×6km scale in summer,and 2km×2km to 6km×6km scale in fall.And 5km×5km scale in autumn showed the best reduction.Increasing green land area can reduce the PM2.5 concentrations when the green area was more than 3km×3km scale in winter and spring,and 5km×5km scale in autumn.Strengthening the protection and expansion of large green patches and improving green patches cluster effect can significantly reduce the concentration of PM10 in 2km×2km to 6km×6km scale in autumn,especially in 3km×3km scale.Increasing the large plaque area and improving the patches aggregation degree can significantly reduce PM2.5 concentration in 4km×4km and 5km×5km scale in winter.The PM10 concentration was significantly reduced in 1km×1km scale in winter when the green land patch shape became more complex.And the concentration of PM2.5 was reduced using the same way in 1km×1km scale in spring.The results can provided a quantitative basis for planning design of multiple scale urban green space.