基于SOM和多元分析的滇池沉积物污染特征空间模式研究

联合运用层次聚类分析(HCA)、判别分析(DA)和自组织映射神经网络(SOM)3种数值方法,对滇池2008—2010年17个底泥监测点位(10个常规点位及7个新增点位)9种污染物进行空间差异性和相似性分析,并评价各指标在空间的分布特征及监测点代表性.结果表明:滇池沉积物整体污染程度为草海>外海中部及南部>外海北部.As、Hg、Pb、Cd、Cu和Zn污染最严重的点位是断桥;草海中心的凯氏氮污染最严重,其他指标污染水平仅次于断桥;Cr和TP污染最严重的点位是新增点位盘龙江2;海埂是全局污染最轻的点位.现有的常规监测点位对整体污染特征的代表性较弱,建议取消异质性最低的白鱼口、观音山西、观音山东和罗家营站点;考虑污染特征和监测点位空间分布的均匀性,建议将盘龙江2、海埂和马料河设为常规监测点位.     

工业污染源综合评价层次分析法

根据层次分析法原理，可将污染源分解成污染要素，再分解为影响因子再分解为次级因子层，构造污染源评价的多层次评价结构模型，根据评价对象的性质和特点，建立指标体系，再据确定的取值规则，以各因子层构成准则层，以各污染源构成方案层，建立判断矩阵计算总排序权值，进行污染源综合评价。     

赋权相关分析与环境设施优化选择

在环境质量评价及环境设施优化选择过程中，客观地设计分析模型，并合理地选择权系数是问题的关键和难点。如果处理不当，将会得出与客观实际完全相反的结果。从而影响决策的准确性，造成不应有的损失。本文以灰色系统理论和层次分析法为基础，提出利用二步层次分析法确定权系数的多指标相关分析方法，并将其应用于烟气处理设施的综合性能评价之中。实例分析表明，该方法具有赋权合理、计算简便、一致性程度高、受决策者主观臆断影响小，评价结果可靠等特点。因此，该方法用于环境设施优化选择过程是可行的。     

关于建立许家峪生态农业示范村的可行性研究

生态农业示范村建设是进行综合生态农业示范体系研究的基础,也是神态农业经营理念和技术推广的重要途径。因此,地理、交通、自然和人文环境的选择,生产经营模式的确定对生态农业经营效益和示范影响效果至关重要。本文通过对许家峪村的现状和作为冀东生态农业示范村的优势和存在问题以及适宜的经营模式进行了剖析和阐述。     

对财务经济分析体系发展的初探

随着我国社会主义市场经济体制的建立和发展,企业将面临着一个日益完善的市场经济体系,这就要求企业的行为要更加规范。于是能够评价、分析企业盈利能力、生存能力、发展能力等各项指标的财务分析体系,就显得尤为重要了。本文主要从现行条件下财务分析体系入手,从财务分析体系的内容和发展前景两个方面,阐述了对财务分析体系发展的几点初步认识。     

Current and Future Strategies for Water and Wastewater Management of Istanbul City

Istanbul has experienced rapid increases in population to more than 12 million people, which has created infrastructure problems of water supply and wastewater treatment and disposal. In this article, the achievements and approaches of the Istanbul Water and Sewerage Administration (ISKI) to solve the water shortage problem and to improve services are summarized. Istanbul had a very severe water shortage problem in 1994 because of ignorance of the implementation of the needed projects. After reviewing the reasons and causes of the problem, new priority criteria adopted after 1994 are given. Following the implementation of the projects determined according to the aforementioned criteria, water supplied has exceeded the water demand. The added capacity is equal to one to three times of the capacity built up to 1994 for water treatment, service reservoirs, pumping stations, transmission lines, and the water distribution network; water quality has been improved the meet local and international potable water standards. Unaccounted for water has been reduced from 60% to 27%. The percentage of treated wastewater has been increased from 10% to 90% in 8 years, resulting in drastic improvements and rehabilitation of the Golden Horn and coastal water quality. Through improved customer services, complaints were reduced from 33% in 1994 to 0.3%. Some of the main criteria and the approaches behind this success are summarized. Published online     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Development of a Methodology for Selecting Criteria and Indicators of Sustainable Forest Management: A Case Study on Participatory Assessment

This paper describes an application of multiple criteria analysis (MCA) in assessing criteria and indicators adapted for a particular forest management unit. The methods include: ranking, rating, and pairwise comparisons. These methods were used in a participatory decision-making environment where a team representing various stakeholders and professionals used their expert opinions and judgements in assessing different criteria and indicators (C&I) on the one hand, and how suitable and applicable they are to a forest management unit on the other. A forest concession located in Kalimantan, Indonesia, was used as the site for the case study. Results from the study show that the multicriteria methods are effective tools that can be used as structured decision aids to evaluate, prioritize, and select sets of C&I for a particular forest management unit. Ranking and rating approaches can be used as a screening tool to develop an initial list of C&I. Pairwise comparison, on the other hand, can be used as a finer filter to further reduce the list. In addition to using these three MCA methods, the study also examines two commonly used group decision-making techniques, the Delphi method and the nominal group technique. Feedback received from the participants indicates that the methods are transparent, easy to implement, and provide a convenient environment for participatory decision-making.     

Using Decision Analysis to Choose Phosphorus Targets for Lake Erie

Lake Erie water quality has improved dramatically since the degraded conditions of the 1960s. Additional gains could be made, but at the expense of further investment and reductions in fishery productivity. In facing such cross-jurisdictional issues, natural resource managers in Canada and the United States must grapple with conflicting objectives and important uncertainties, while considering the priorities of the public that live in the basin. The techniques and tools of decision analysis have been used successfully to deal with such decision problems in a range of environmental settings, but infrequently in the Great Lakes. The objective of this paper is to illustrate how such techniques might be brought to bear on an important, real decision currently facing Lake Erie resource managers and stakeholders: the choice of new phosphorus loading targets for the lake. The heart of our approach is a systematic elicitation of stakeholder preferences and an investigation of the degree to which different phosphorus-loading policies might satisfy ecosystem objectives. Results show that there are potential benefits to changing the historical policy of reducing phosphorus loads in Lake Erie.     

Methodological Development of an Index of Coastal Water Quality: Application in a Tourist Area

With the aim of obtaining an index of coastal water quality, a methodological procedure based on numerical classification and discriminant analysis is presented. The procedure was applied to nutrient data (ammonia, nitrite, nitrate, and phosphate) analyzed along the coastal waters of a Spanish tourist area. Using numerical classification, three levels of nutrient loading were revealed, characterizing oligotrophic, mesotrophic, and potentially eutrophic waters. Discriminant analysis was shown to be an effective methodological tool in the discrimination between trophic groups. For every group, the discriminant procedure generated the centroids. The centroids representing oligotrophic and potentially eutrophic conditions were used to establish the two extremes of the continuum of mesotrophic conditions in these coastal waters: Standardizing values from -1 to 1, the centroids for oligotrophic and potentially eutrophic waters yielded an interval that defined the range of mesotrophic conditions. This interval is proposed as a water quality index. The ability of the coastal water quality index to successfully predict mesotrophic conditions was proved with random samples.