北方城市绿地对大气颗粒物浓度的削减作用对比研究

尽管城市绿地能够改善空气质量,但由于实践中缺乏统一的绿地分类系统,很难从优化绿地植被结构的角度出发调节城市空气质量。因此,为了探究北方城市不同绿地削减大气颗粒物浓度效果的差异,构建了一套融入植被结构因子和物种组成的绿地分类系统,基于该分类系统,在北京、西安、宝鸡选取了5类共同常见的植被结构绿地类型,通过卫星图像判读与实地监测相结合的方式,探究了不同本底环境、植被结构、植物多样性、气象因子和时间因子对大气颗粒物浓度(PM_2.5与PM₁₀)的影响。结果表明:(1)城市绿地率对大气颗粒物浓度造成显著影响,绿地率越高的本底环境内颗粒物浓度越低,即多绿本底<灰绿参半本底<灰色本底;(2)植被结构和植物多样性水平显著影响绿地的滞尘能力,北方城市中半开敞绿地的滞尘能力最好,其次为半闭合绿地与闭合绿地,开敞绿地滞尘能力最弱,植物多样性的增加将导致绿地内颗粒物浓度增加;(3)不同植被结构绿地内的大气颗粒物浓度受气象因素的显著影响,随温度和风速的增大而减小,随湿度的增大而增大;(4)北方城市绿地大气颗粒物浓度存在明显的季节和日变化规律,一年内大气颗粒物浓度在夏季最低,冬季最高;一天之内颗粒物浓度在8:00-10:00最低。上述研究结果以期为今后不同本底环境下以削减大气颗粒物浓度为导向的北方城市绿地规划与设计提供理论依据和实践方法。

Comparison of the reduction effects of green space on atmospheric particulate matter concentration in northern cities

Although urban green space can make the air cleaner, the lack of a system to classify green space makes it difficult to improve air quality from the perspective of optimizing vegetation structure in practice. A classification system of green space that incorporates vegetation structure and species composition was constructed to explore the differences in reducing PM concentration among green spaces of different structures in northern cities. Based on the system, five common types of vegetation structure green spaces were selected in each of the three cities of Beijing, Xi''an, and Baoji. The effects of different background environments, vegetation structure, plant diversity, meteorological factors, and time factors on the concentrations of atmospheric particulate matter (PM_2.5 and PM₁₀) were explored by combining interpretation satellite imagery and field measurements. The results are as follows: (1) Urban green space rate has a significant impact on the concentration of atmospheric particulate matter: the background environment with higher green space rate has lower concentration of particulate matter, which means the PM concentration in different background environments ascends in this order: green background, gray-green background, and gray background. (2) Vegetation structure and plant diversity significantly affect the dust-retention capacity of green spaces. As for various vegetation structures, the dust-retention capacity of the semi-open green space in northern cities marks the top, followed by semi-closed green space and closed green space, with the open green space at the bottom. When plant species diversity increases, the particulate matter concentration in the green space increases. (3) The concentration of atmospheric particulate matter in green spaces is significantly influenced by meteorological factors, decreasing with higher temperature and wind speed, and increasing with higher humidity. (4) There are obviously seasonal and daily changes in the concentration of atmospheric particulate matter in green spaces in northern cities. In the same year, the atmospheric particulate matter concentration is lowest in summer and highest in winter. The concentration of particulate matter is the lowest in the morning in one day. The results are expected to be used as the theoretical basis for future planning and design of green space concerned about atmospheric particulate matter reduction under different background environments.