半干旱区城市绿地及树种消减大气颗粒物机制研究

Severe particulate matter pollution in the atmosphere caused by high-level urbanization has led to a series of environmental and health problems. Urban green spaces and trees can capture atmospheric particulates effectively, and most study focus on investigating the effects of landscape plants on atmospheric particulate absorption at individual and community level. However, few of them concentrated on the reduction mechanism. In this study, based on the survey of air quality and vegetation background in Hohhot, a city located at the typical semi-arid region of Inner Mongolia, we will explore the absorption mechanism of atmospheric particulates from multiple dimensions using scanning electron microscopy, environmental magnetism method, absorption spectroscopy technology, kinetic method, model building method and so forth. First, at the individual level, we plan to discuss the particulate matter absorbing by leaves from diffenrt aspects, such as the morphology, ecological characteristics, magnetic parameters and adsorption properties. Second, at the community level, we will explore the correlation between the characteristics of road green belt, artificial forest community and natural forest community in parks, the magnetic parameters of leaves, the content of pollutants in leaves and the concentration of atmospheric particulates. Finally, from the perspective of space pattern, we will investigate the remote sensing information, landscape indices of green space, and build the relationship between atmospheric particulate concentration using PLS model and artificial neural network model. Integrating multi-dimensional research results, we hope to reveal the mechanism of urban green spaces and tree species on atmospheric particulates absorption, and propose useful planning strategies of plant community structure and green spaces layout with corresponding technical countermeasures, which can reduce the atmosphere particulates pollution effectively, and furthermore, provide theoretical and practical references for the improvement of urban ecological environment and the construction of livable city.

高度城市化使得大气颗粒物污染加重，由此引发了环境、健康等一系列问题。城市绿地和树木能有效捕捉大气颗粒物，国内外对园林植物个体、群落吸滞大气颗粒物的效应研究较多，而对其消减机制探讨较少。本研究拟通过对内蒙古半干旱区城市呼和浩特的空气质量、植被等进行调查，利用扫描电镜法、环境磁学法、吸收光谱法、动力学法、模型构建法等多种研究方法，从个体角度研究树种叶吸滞颗粒物的形态、生态特征、磁学参数与吸附特性等；从群体角度探测道路绿化带、公园人工林和天然林植物群落特征、树种叶磁学参数、叶内污染物含量与大气颗粒物浓度的相关性；从空间角度分析绿地的遥感信息、景观指数等，借助PLS模型和人工神经网络模型构建与大气颗粒物浓度的关系；以期从多维度探究树种、植物群落对大气颗粒物的吸滞机理，提出高效吸滞颗粒物的植物群落结构、绿地布局规划策略和技术对策，为改善当地生态环境、营造宜居城市提供科学论据和现实参考。

城市绿地和树木能显著的消减大气颗粒物（PM），对其吸滞机制的探究具有重要意义。为了探讨半干旱区城市树种及绿地的生态性能、吸滞PM能力，本研究从树种个体角度，利用扫描电镜法、吸收光谱法、环境磁学法等分析了目标城市10种常见树种消减PM的叶微形态特征、磁学参数和叶面和叶内污染物吸附特征，发现了梓树、金叶榆、西府海棠等叶微态结构粗糙、气孔密集的树种吸滞PM和重金属能力较强，叶表面附属物在滞尘、气孔作为颗粒物进入内部的重要通道在吸污方面发挥着重要作用，而树种叶吸滞17种金属的能力与植物物候期密切相关，从而阐明了树种叶片吸附PM的机理；且梓树以吸滞细磁畴磁性PM为主，而其它树种以粗磁畴磁性PM的吸滞为主，而西府海棠叶对Pb溶液的吸附率最好，筛选出了最佳吸污抗污树种。从植物群体出发角，利用田野调查法、环境磁学法、X射线能谱法等探明道路和公园绿地植物群落组成、结构在时间和空间上对PM的消减机制，研究结果显示了路侧绿带对PM的消减率随水平距离的增加呈“单峰或双峰”变化，以水平距离45m处绿地对颗粒物的消减效果最佳；4种植物群落结构中消减能力以乔-灌-草结构最强；以林冠密度50%处消减率最高。分析了不同污染区公园8种绿地植物群落结构的PM消减能力，发现以针阔混交林、乔草结构、灌草结构消减能力最强；绿地群落结构消减颗粒物能力因污染程度的不同而有所差异，在中度、轻度污染区消减能力较强，重度污染区消减能力相对较弱，且含有高大针叶常绿乔木的混交林和垂直方向层次丰富的绿地植物群落结构消减颗粒物综合能力较强。从绿地空间分布和模型构建角度，利用Envi-MET、SUV支持向量机模型构建法、GIS法等分析城市绿地PM消减率及道路、公园植物群落的实测和模拟效果，提出合理的城市绿地最佳构建模式，拓展了绿地消减大气颗粒物研究的地域范围，指导内蒙古半干旱区城市绿地改善空气质量的规划、设计和建设。