上海浦东新区绿地系统研究—分布格局、生态系统特征及服务功能
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摘要
城市绿地系统是城市内唯一有生命的基础设施,不仅能美化环境,而且具有吸收空气中的有害气体、吸附颗粒物、吸声降噪、城市碳汇等多种生态功能,是城市生态环境及可持续发展的重要基础,也是提升居民健康和生活质量的重要因素。近年来,对城市绿地生态和社会服务功能开展定量的、多学科的综合研究已是国内外学者的共识,成为城市生态研究的热点。本论文以上海浦东新区绿地系统作为研究对象,宏观上应用GIS和人工神经网络研究了绿地系统的格局分布,微观上分析评价了常见绿化植物叶片抗酸能力及绿地土壤质量等生态系统特征,并应用被动式采样等方法定量分析了浦东新区典型绿地对大气污染物的净化效益,用调查问卷的方法研究了浦东新区公园的服务人群和游客需求。本文旨在建立城市绿地生态和社会服务功能研究的新方法,阐明绿地在改善城市生态环境、提高居民生活质量中发挥的作用,为浦东新区绿化规划、建设和改造提供基础数据,以期发挥更好的生态和社会服务功能。
     在对绿地系统分布格局的研究中,应用GIS、人工神经网络模型等工具,实现了对浦东新区的绿量、景观格局等指标的空间格局分析,并进行了总体评价。结果发现绿化格局状况较好的区域为中部区域,西部沿江区域人口密集,绿地破碎化程度较高,而东部非建成区的绿化面积有限。因此对不同的区域提出不同的绿地规划和发展的建议,总体达到楔状、放射型的绿地生态体系,平衡浦东新区绿地整体的生态及社会服务功能。
     对绿地生态系统特征的研究主要从植物和土壤两方面展开:通过对浦东新区6种常见绿化植物的生化指标、含硫量、含氮量分析,发现植物叶片细胞液的pH值和缓冲能力是植物吸收净化空气中SO_2、NO_x的主要控制因素,植物叶片pH值越高、酸缓冲能力越强,越有利于吸收空气中SO_2、NO_x等酸性气态污染物。通过对典型绿地土壤样点理化性质、养分状况、重金属污染和生物酶活性的分析测试,发现浦东新区绿地土壤的理化性状和养分状况总体属于中等偏下的状况,各重金属指标总体含量较低,但在公路绿地土壤中的含量偏高。通过研究酶活性与土壤其它质量因子的关系,建立了酶活性指示土壤生态质量的相对分级评定方法,对新区土壤质量进行了评价和验证,证明了用酶活性评价土壤生态质量的可行性和有效性。
     对绿地系统的服务功能研究主要从生态服务功能和社会服务功能两方面开展研究。本论文首先选择了浦东新区有代表性的交通绿地和公园绿地作为典型绿地,通过与无植被的裸地进行对比分析,定量分析了典型绿地阻挡吸收大气污染物的生态服务功能。研究结果表明:公园绿地和交通绿地中的绿色植物可通过阻挡、吸收等作用降低由交通污染产生的约15-50%的TSP、8-20%的NO_2、和10-25%的SO_2污染,但是不同绿地之间以及同一绿地不同季节间,其污染物净化效果存在差异。
     对开阔道路旁侧绿化带对大气污染物的净化过程进行了模型模拟和解析,建立了污染物底物浓度指数衰减模型,并探讨了衰减速率常数k与绿地结构和状况指标(郁闭度、疏透度、绿量密度)的关系,得到各指标最佳配置范围,并对典型交通绿地进行初步的植物配置:在300m2的交通绿化带样地中应配置12-15株乔木,30株左右大灌木及80株左右小灌木,并搭配至少100m2的草本植物;乔木、大灌木、小灌木的比例维持在1:2:5左右,草本植物种植面积达到30%以上。这种植物配置方式基本可以达到郁闭度75%、疏透度30%,绿量密度合适的疏透式植物群落。
     在对公园绿地对大气污染物净化研究中引入了混合效应模型,分析城市公园周边环境的4类主要影响因素(气象、空间、污染源、植被)对污染物效果的影响,结果表明,公园的植物配置情况和污染物扩散距离是影响公园内污染物衰减的关键因素。在此基础上,估算出浦东新区绿地系统对大气污染物净化的贡献:绿地系统对TSP的净化贡献约为9.1%,对SO_2的净化贡献约为5.3%,对NO_2的净化贡献约为2.6%。
     对社会服务功能的研究是通过对浦东新区主要公园的的游客群体进行问卷调查进行的,发现公园游客主体特征为50岁以上退休中老年人,收入偏低,每天独自步行或者骑车30分钟以内来公园进行锻炼健身或休闲娱乐活动。通过建立回归模型,筛选“老龄因子”,将16个公园根据不同服务人群和功能的分为三类,根据每类公园服务人群对公园的使用偏好和需求,提出优化公园设施配置和设计建议,提升城市公园的社会服务功能。
Green spaces are the only alive infrastructure in urban area, not only used for beautifying urban environment, but also for providing ecosystem services such as absorbing gaseous pollutants, removing particles, preventing noise and carbon sequestration. Green spaces are seen as the basis of urban environment sustainable development for residents’life quality, and multi-discipline researches on quantifying ecosystem and social services of urban green spaces had become hot topics of recent urban studies.
     This dissertation looks at green spaces in Pudong district Shanghai, using GIS and ANN model to inllustrate the green spaces pattern and distribution, quantifying air quality improvement by passive and active samplers, and analyzing the population and needs of urban park visitors by questionnaire survey, to explore the methodology of characterizing ecosystem and social services providing by urban green spaces, and demonstrate the function of improving urban environment and life quality by urban vegetations. The dissertation will provide fundamental data for green space planning and construction, and maximize their social and ecosystem benefits.
     The indicator of green-biomass and landscape patterns, and GIS and ANN are introduced to analyze green space pattern and distribution of Pudong district. Results show that middle area has the best green conditions. For west area, it should make a better maintenance work, and increase green-biomass by roof planting; and the suggestions for east area are mainly keeping a considerable green-biomass density. For the whole Pudong District, the green space pattern should be radial distributed to balance the ecosystem and social functions.
     By means of analyzing biological and chemical indicators, sulfur contents and nitrogen contents of prevailing vegetations in this area, the dissertation reveals primarily that the marked correlation among pH of leaves' cell sap, buffering capacity and sulfur and nitrogen contents, which are also the determinants that affect the plants in absorbing sulfur compounds and nitrogen compounds in the air. And higher pH in leaves and greater acidic buffering capacity both help to absorb acidic gases in the air such as SO_2 and NOx.
     The urban soil indicators such as chemical and physical indicators, nutrient condition, heavy metal pollutants, and enzyme activities are measured among soil samples in Pudong District. The results show that the structure and nutrient condition of urban soil are not good; the pollution of heavy metal is minor, but the soil closed to road has a higher level than other samples. The standard of evaluating soil quality by enzyme activity are set up using comparison of enzyme activity and other indicators of soil, then soil quality is classified by this enzyme activity method and the efficiency of this method is justified by existing experimental data.
     Typical green spaces are selected as samples in Pudong District, the ecosystem functions of vegetations such as absorbing gaseous pollutants, removing particles and preventing noise were quantified by using both passive and active sampling approaches. The results show that green spaces are effectively in removing pollutants for 10-25% SO_2, 8-20% NO_2, and 15-50% TSP. However, the removal functions are varied from place to place, and in different seasons.
     Traffic green spaces are important component of urban green space system. To analysis the impact that it's role on the pollutants declining effects, this dissertation measures the distributing profile of TSP in the greenbelts and set up an EA model to describe the distributing behavior of TSP decline in the traffic greenbelts. The correlation between attenuation coefficient k and green space indicators such as canopy density, shelterbelt porosity and green-biomass density is discussed to characterize the optimal intervals for green space construction. And the guidelines for planting are suggested: 12-15 trees, 30 large shrubs, 80 small shrubs and 100m2 herbage should be planted in 300m2 green space site. The planting structure could get the canopy density of 75%, shelterbelt porosity 30% and proper green-biomass density within the site.
     A mixed-effects model is applied for characterizing air pollutants attenuation in urban parks. Results prove that green-biomass density and pollutants diffusion distance are significant predictor influencing pollutants removal rates. Therefore, on the assumption that Pudong District could be regarded as a large urban park, the air quality improvement due to pollutants eliminated by urban vegetations could be estimated: the results imply that in summer, urban vegetations of Pudong District could contribute 9.1% of the TSP removal, 5.3% of the SO_2 and 2.6% of the NO_2.
     Questionnaire survey are conducted in 16 parks of Pudong District, the results show that the main features of park visitors are old people over 50 years old, low-to-middle income, going to parks alone by walk or bicycle almost everyday for doing exercising or relaxing. The dissertation set up a regression model and choose“older age factor”to classify 16 urban parks into 3 groups. Every group of parks have a special service population, and visitors have their unique patterns to use these parks. So suggestion for different groups of parks are provided, so as to improve social benefits of urban parks in Pudong district.
引文
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