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.      

生物表面活性剂产生菌犁头霉菌(Absidia orchidis)的筛选及发酵条件优化

采用植物油为唯一碳源,设计选择培养基,从饭店下水道污泥中筛选出生物表面活性剂产生菌.结果分离到12株菌,其中一株能使发酵液的表面张力值从68 mN·m-1降低到34.5 mN·m-1,具有开发潜力,被选出作进一步的研究.该菌株经鉴定为犁头霉菌(Absidia orchidis).通过正交试验对犁头霉菌的培养条件进行优化,其优化培养条件为:植物油3.6 g·L-1,KH2PO412.1 g·L-1,Na2HPO45 g·L-1,(NH4)2SO4 1 g·L-1,NaNO32 g·L-1,酵母浸膏0.1 g·L-1,MgSO4·7H2O 0.15 g·L-1,NaCl 5 g·L-1,CaCl2 0.1 g·L-1,EDTA 1 g·L-1,KI 0.83μg·L-1,H3PO4 0.01μg·L-1,CoCl2·6H2O 0.048μg·L-1,MnSO4·H2O 0.312μg·L-1,Na2 MoO4·2H2O 0.048μg·L-1,ZnCl2 0.287μg·L-1,CuSO4·5H2O 0.125μg·L-1,初始pH值8,接种量6%.发酵70h时可获得生物表面活性剂的最大收获量,此时发酵液中生物表面活性剂的相对浓度达402倍.     

Fe3+掺杂TiO2薄膜的制备及光催化降解甲醛的研究

采用溶胶-凝胶法制备Fe3+掺杂的TiO2薄膜光催化剂,进行甲醛的光催化实验,考察Fe3+掺杂量、薄膜焙烧温度及溶胶体系pH值对光催化性能的影响。结果表明,Fe3+掺杂量为1.0%,焙烧温度500℃1h,加硝酸溶胶体系pH=4时,Fe3+掺杂TiO2薄膜光催化活性最高。     

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。     

SBR法处理豆制品废水工艺条件的研究

用SBR法处理豆制品废水的试验表明,该系统具有较好的抗负荷冲击能力,进水COD在300～2000 mg/L之间变化,对系统不造成任何影响;考察了曝气时间、曝气量和污泥浓度等对去除效果的影响,试验结果表明,曝气时间和曝气量对处理效果影响很大,确定该反应系统最佳曝气时间是8 h,适宜的曝气量是800 L/h,而污泥浓度控制在4000 mg/L左右时,处理效率最高,采用进水顶出水的排水方式是可行的,确定系统的最佳排水比是3/5.厌氧段的插入可以减少剩余污泥的产量.     

高浊度污水快速净化新技术

介绍了一种快速净化高浊度污水的新技术,该技术根据化学强化一级处理(chemically enhanced primary treatment,CEPT)技术、闪速混合(flash mixing)技术、旋流和点涡流絮凝技术、悬浮泥层过滤技术和过滤水力学原理等理论,采用物理化学法去除污水中的有机污染物和其他有害杂质,其有着流程简单可靠、投资和运行费用低、占地少、净化效果好的优势.     

重金属离子存在下腐植酸和芘之间的相互作用

建立并验证了腐植酸(HA)和芘结合常数(Koc)测定的荧光猝灭法,进而研究了重金属离子对HA和芘相互作用的影响,测定了重金属离子存在下HA和芘之间的Koc.结果表明:纯化后的HA是分子质量较小的部分,水溶性较高,具有羟基、羧基和碳氧键等极性基团;HA利用其分子中的羟基、羧基、碳氧键等基团和重金属离子产生络合作用,这种络合作用影响了HA的结构;随着重金属离子浓度的增大,Koc遵循先增大,再减小,最后趋于不变的趋势.     

运用QSPR预测有机磷农药的色谱保留值

通过计算43种有机磷农药的各种结构参数,运用多元线性回归分析方法比较了适用于有机磷农药色谱保留值的定量关系表达式,建立了有机磷农药结构参数对色谱保留值的QSPR模型.模型分析表明:磷酸酯与硫逐磷酸酯两类有机磷农药的模型非交叉验证相关系数R2分别为0.991和0.998,标准误差SE分别为0.0539和0.2874,交叉验证相关系数Q2分别为0.976和0.990,标准偏差Scv分别为0.086和0.610.在已知磷酸酯与硫逐磷酸酯两类有机磷农药结构参数的情况下,此模型可有助于有机磷农药的色谱分析.     

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.