武汉市典型道旁绿地消减空气细微颗粒物的作用研究

将武汉市洪山区巡司河风情公园作为典型道旁绿化带，通过在其中4种结构绿地（草坪、疏林、密林、广场）内设置监测点，监测分析不同结构绿地内PM_2.5和PM₁₀质量浓度日变化规律，以揭示不同结构道旁绿地对空气细微颗粒物的消减作用及其影响因素。结果表明:1）PM_2.5和PM₁₀浓度日变化趋势一致，呈现“单峰单谷”型，其质量浓度在9:00达到最高值，随后开始下降，至15:00达到最低值，之后一直呈上升趋势；2）4种绿地对粉尘颗粒物的消减作用存在明显差异，PM_2.5和PM₁₀的消减率大小排序一致，表现为密林>疏林>草坪>广场，表明郁闭度高的多复层结构的植物配置模式对空气颗粒污染物的消减作用明显优于单层结构；3）在空间变化上，PM_2.5和PM₁₀质量浓度的消减率在一定范围内随绿化带宽度的增加而升高，当宽度在15~25 m时，能较好地消减空气中的细微颗粒物浓度；4）4种结构绿地内PM_2.5和PM₁₀的质量浓度受环境因素的影响，均与温度呈显著负相关（P<0.01），与相对湿度呈显著正相关（P<0.01），与风速和车流量的相关性不显著。

Effect of Typical Roadside Green Spaces on the Reduction of Air Fine Particles in Wuhan

In this study,the Xunsi River Customs Park in Hongshan District of Wuhan was selected as a typical roadside greenbelt to examine the effect on the reduction of air fine particles of the roadside green space with different structures and its influencing factors.The monitoring points in four structural green spaces (turf,sparse forest,jungle,and square) were set up to detect the daily variations of PM2.5 and PM10 mass concentration.The results showed that 1) the diurnal variation trends of PM_2.5 and PM₁₀ concentrations were consistent,both showing “single peak and single valley” type,the mass concentration reached the peak value around 9:00,then began to decline and reached the lowest value at 15:00,and increased after then.2) There were significant differences in the reduction of dust particles in the four green spaces.The reduction rates of PM_2.5 and PM₁₀ were consistently ranked as dense forests>sparse forests>lawns>square,indicating that plant configuration patterns of multiple complex structures with high canopy closure was significantly better than those with single-layer structures in reduction of airborne particulate pollutants.3) In the spatial variation,the reduction rates of PM_2.5 and PM₁₀ concentrations increased with the increase of green belt width within a certain range,and the width of 15-25 m was better in reducing the fine particle concentration in air.4) The mass concentrations of PM_2.5 and PM₁₀ in the four green spaces were affected by environmental factors,and both were significantly and negatively correlated with temperature (P<0.01),positively correlated with relative humidity (P<0.01),and not correlated with wind speed and traffic flow.