Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

TUGAI: An Integrated Simulation Tool for Ecological Assessment of Alternative Water Management Strategies in a Degraded River Delta

The development of ecologically sound water allocation strategies that account for the needs of riverine ecosystems is a pressing issue, especially in semiarid river basins. In the Aral Sea Basin, a search for strategies to mitigate ecological and socioeconomic deterioration has been in process since the early 1990s. The Geographic Information System–based simulation tool TUGAI has been developed to support the policy determination process by providing a simple, problem-oriented method to assess ecological effects of alternative water management strategies for the Amudarya River. It combines a multiobjective water allocation model with simple, spatially explicit statistical and rule-based models of landscape dynamics. Changes in environmental conditions are evaluated by a fuzzy habitat suitability index for Populus euphratica, which is the dominant species of the characteristic riverine Tugai forests. Water management scenarios can be developed by altering spatiotemporal water distribution in the delta area or the amount of water inflow into the delta. Outcomes of scenario analysis are qualitative comparisons of the ecological effects of different options for a time period of up to 28 years. The given approach utilizes different types of knowledge, from quantitative hydrological data to qualitative local expert knowledge. The main purpose of the tool is to integrate the knowledge in a comprehensive way to make it available for discussions on alternative policies in moderated workshops with stakeholders. In this article, the modules of the tool, their integration, and three hypothetical scenarios are presented. Based on the experience gained when developing the TUGAI tool, we propose that the general framework can be transferred to other areas where tradeoffs in water allocation between the environment and other water users are of major concern. The potential for a simulation tool to structure and inform a complex resource management situation by involving local experts and stakeholders in the development of possible future scenarios will become increasingly valuable for transparent and participatory resource management.     

生活垃圾焚烧飞灰在饰面砖中资源化应用技术

分析了飞灰的性质,利用飞灰、红泥及缸砂研制饰面砖,研究了飞灰对饰面砖性能及微观结构的影响,并对其安全性进行了评价。结果表明:飞灰主要化学成分是CaO、SiO2、Al2O3,构成SiO2-Al22O3-金属氧化物体系,可用作饰面砖的原材料;当飞灰掺加量为20%时,饰面砖表现出良好的性能:抗压强度19·2MPa,吸水率7·2%,表观质量达到一等品要求;与飞灰相比,饰面砖中重金属浸出能力大大降低:As、Pb、Ni、Cr、Cu、Hg、Cd水平振荡浸出毒性未检测出,Zn的水平振荡浸出值下降到飞灰中的0·014倍,Hg、Cd有效浸出毒性未检测出,As、Pb、Ni、Cr、Cu、Zn的有效浸出毒性分别下降到飞灰中的0·056、0·001、0·067、0·058、0·056、0·029倍。     

楚雄德胜钢铁公司烧结机尾除尘改造实践

介绍楚雄德胜钢铁公司19·6m2烧结机尾除尘系统改造工程中使用三电极电除尘器的工艺及有关设计技术问题,并根据使用效果进行分析总结。结果表明,在设计参数选择恰当的情况下,三电极电除尘器对烧结烟气有较好的除尘效果,这些经验和操作中存在的问题供烧结机尾除尘工程设计参考。     

滇池流域磷循环系统的物质流分析

研究营养元素在社会经济系统中的物质代谢结构及特征,是有效预防和控制地表水体富营养化的关键性分析技术之一.以滇池流域磷循环为研究案例,运用物质流分析方法建立了2000年流域静态物质流模型(PHOSFAD),并在此基础上识别出流域磷循环系统的总体结构特征,以及资源开采、化工生产、农业种植、畜禽养殖、居民生活等生产和消费部门的物质利用效率特征,为科学防治滇池水体富营养化提供了重要决策依据和参考.     

冬季动态槽式堆肥温度的空间变异

以鲜鸡粪、蘑菇渣和污泥按照体积比3∶1∶1混合进行动态堆肥模拟试验.堆肥槽沿物料前进方向分为7个部分,对每个部分按等间距分别做5个水平方向上切分和5个垂直方向上切分,在形成的125个交叉点上进行温度监测.研究结果表明,第1天的混合物料温度在同一层中变异很小,不同层之间略有差异.随着动态过程的进行,同一层温度变异逐渐增大,从第一天相差1～3℃,增加到相差30～40℃,靠近墙体的堆料温度较低,远离墙体的温度较高.随着堆肥时间延长,差异增大.机械翻堆能起到通风的作用,同时使每一个堆方的堆料在纵向方向上上下混合,但达不到横向混匀,因此,靠近墙体两侧的堆料始终处于较低的温度,只有中部能达到较高的温度,以堆肥温度50℃作为无害化指标,自墙体向中心方向的1m为没有达到无害化厚度,无害化体积占堆肥总体积50%.整个动态堆肥过程符合二级动力学方程.     

基于GIS的北京市妫水河流域水土流失的初步分析

基于ArcGIS空间分析平台和ERDAS空间建模平台,利用水土流失综合指数法,分别以坡度、植被覆盖度和土地利用类型为主要背景因子,分析了北京市妫水河流域水土流失的空间背景特征.结果表明,妫水河流域水土流失的空间背景特征是缓坡、低植被覆盖度和疏林灌草地,而这些特征正是妫水河流域山前洪冲积扇地区的主要特点,缓坡、低植被覆盖度(不考虑城市建成区)和疏林灌草地也主要集中在流域内山前洪冲积扇地区.并提出防治妫水河流域水土流失的有效措施.      

重庆市大气污染物的空间统计分析

利用空间统计分析方法(spatial statistics analysis),借助GIS,分析了重庆市3种主要大气污染物TSP,SO₂和NO_x质量浓度在空间上的分布特点.研究表明,在"九五"期间和2002年2个时期,重庆市大气污染物在空间上均呈不均衡分布.整体上,SO₂的空间自相关性很强,属集中分布模式;TSP的空间自相关性较弱,属于随机分布模式;NO_x处于二者之间.局部相关性分析表明,大部分区县的大气污染物之间相关性较弱.此外,利用缓冲区和内插浓度表面法分析了2个时期的污染物质量浓度随离行政中心距离变化的趋势,发现ρ(TSP)和ρ(SO₂)在各地带内均有明显削减,而ρ(NO_x)削减不显著;ρ(SO₂)和ρ(NO_x)随距行政中心距离增大下降,但ρ(TSP)随距离增大而增加.3种污染物质量浓度都在离行政中心50～60 km的地带发生明显变化,由此得出目前重庆市大气污染物空间分布的特征距离为50～60km.      

一株反硝化菌的分离鉴定和系统发育分析

从反硝化反应器中分离到一株异养型兼氧反硝化细菌,命名为菌株JIN1,分离菌株为革兰氏染色阴性杆状。茵落颜色为乳白色。该菌株能以硝酸钠为唯一氮源进行反硝化作用并产生亚硝酸。部分长度的16SrDNA序列分析表明,分离菌株JIN1与Aquaspirillum菌具有99%相似,与Microvirgulaaerodenitrificans菌具有99%相似。其生化性状与Aquaspirillum菌不相符。系统发育学分析表明菌株JIN1与Microvirgulaaerodenitrificans菌关系最近。故确认菌株JIN1属Microvirgulaaerodenitrificans菌。     

长江经济带绿色城镇化效率评价及其影响因素——基于多维城镇化视角

本文引入资源和环境因素,以城镇化综合指数为期望产出,运用SBM方向性距离函数测算了2010—2020年长江经济带112个地级市（州）的绿色城镇化效率,并采用空间面板模型和地理探测器对绿色城镇化效率的影响因素进行实证分析。结果表明：长江经济带绿色城镇化效率整体水平不高,下游地区绿色城镇化效率高于上游和中游地区,资源消耗和环境污染是效率损失的主要来源;绿色城镇化效率表现出较为明显的热点—次热点—次冷点—冷点自东向西的带状分布格局,存在显著的空间正相关性。政府财政支出对绿色城镇化效率产生负向影响,外商直接投资和产业结构对提升绿色城镇化效率有显著的促进作用,且三者的影响具有地区差异性;市场力因素有利于绿色城镇化效率的提高。邻近城市间绿色城镇化效率的空间溢出效应明显,且空间溢出效应是长江经济带绿色城镇化效率空间差异的最主要因素,各因素的影响具有协同增强的作用。