企业"绿色度"的模糊评价模型与应用

"绿色度"是绿色的程度或与环境友好的程度.分析了企业"绿色度"绩效评价的理论基础,讨论了在众多因素影响下关于企业"绿色度"绩效评价的指标体系;采用专家法确定各因素权重;运用多层模糊综合评价原理进行系统评价.并通过一个化工厂的实例验证了所建立模型与求解方法的正确性与实用性.     

Characterization of aliphatic hydrocarbons in deep subsurface soils near the outskirts of Beijing, China

Thirty-nine deep subsurface soils( 150—180 cm depth) near the outskirts of Beijing were investagated. The concentrations including n-alkanes from C13 to C36, pristane and phytane were in the range of 0.60 to 170.10μg/g, with a median value of 4.26. Carbon preference index values for n-alkanes ranged from 1.08 to 2.98, with a median value of 1.48. The percentage contribution of “wax” nalkanes was in the range of 6.03%--46.22%. A predominance of odd/even carbon n-alkanes and unresolved complex mixtures with different shapes and ranges were frequently observed. Factor analysis reduced the data set into three principal components and confirming contributions from low ( 19.58% ), medium ( 20.49% ) molecular weight species and long-chain n-alkanes (43.41% ), respectively.Molecular biomarkers such as pristane, phytane, hopanes and steranes were detected. Based on the principal component analysis, the concentration profiles and molecular markers, it was found that the aliphatic hydrocarbons were from both biogenic and anthropogenic sources.     

Phytoplankton Community and Chlorophyll a as Trophic State Indices of Lake Skadar (Montenegro,Balkan) (7 pp)

Background, Aims and Scope Phytoplankton, as a first step in trophic cascades of lakes, can be a good indicator of trophic states, considering that every environmental change affects this community and many species of this community are sensitive to changes, and that they response very quickly. In this study, we tried to assess and predict the trophic state of Lake Skadar according to phytoplankton data.Methods Water samples were collected using Ruttner sampling bottle. Temperature, dissolved oxygen, ph, conductivity and transparence were measured in situ using portable equipment. Nutrients and chlorophyll a were measured using standard spectrophotometric methods. A determination of phytoplankton species was performed using relevant keys and the counting of cells was performed using sedimentation methods.Results and Discussion The species composition of Lake Skadar revealed 95 taxa, with Chlorophyceae and Bacillariophyceae being represented best. According to an average chlorophyll a concentration of 5.9 µg/l, Lake Skadar belongs to the mesotrophic level of the trophic scale. Developed prediction equation for chlorophyll a revealed a good prediction (R2=0.71) and the parameter Secchi depth was primarily correlated with chlorophyll a concentration. Trophic state indices derived from chlorophyll a and transparency, were close together, but both were below the phosphorous index. Values of trophic state indices rank the Lake Skadar as being mesotrophic. This study also showed that indices of diversity based on phytoplankton are weak indicators of trophic status and that they can well characterize only differences between assemblages and associations. According to calculated saprobic indices (ranging from 1.5 to 2.15), Lake Skadar is on betamesosaprobic level of saprobity, which means that it is moderately polluted with organic compounds. Conclusions Total phosphorus is not the main limiting factor for the phytoplankton community in Lake Skadar. Disagreements between chlorophyll and the transparency index, on the one hand, and the total phosphorus index, on the other, suggest that the phytoplankton in Lake Skadar is probably limited by other factors than phosphorus, such as nitrogen, toxic substances or intense zooplankton grazing. According to the majority of investigated parameters and indices derived from phytoplankton data, Lake Skadar is mesotrophic, with tendencies toward eutrophic levels during the summer period. Recommendations and Outlook Long-term monitoring is required for a better estimation of state and the conditions of Lake Skadar. Further studies on factors influencing the phytoplankton community, especially zooplankton grazing and toxic substances, which were not included in this study, should be continued in the future to improve the efficiency of phytoplankton usage in estimating the ecological and trophic conditions of Lake Skadar.     

取代苯乙酮类有机物溶解度和分配系数的测定

本文采用产生柱法测定取代苯乙酮类有机物的水溶解度和正辛醇-水分配系数,与静态法和振荡法测定的水溶解度、摇瓶法测定的正辛醇-水分配系数相比较,证明此方法是可行的,并和分子连接性指数呈良好的相关性。     

阊江河1～6级支流大型底栖无脊椎动物取食功能团演变特征

河流连续性概念(rivercontinuumconcept,RCC)将自然河流生态系统视为物理和生物的连续体,河流物理环境的梯度变化决定了生物的演变格局.为探索自然河流系统受人类干扰后大型底栖无脊椎动物的演变规律,作者于2002年5月、8月、11月对安徽省祁门县阊江河1~6级支流的大型底栖无脊椎动物进行了调查,共获7纲57科101属119种,计8813头,并详细记载了各级支流样点的栖境特点.运用“河流连续性概念”理论分析结果表明该河1~6级支流大型底栖无脊椎动物各取食功能团演变趋势符合该理论,但上游至下游的生物区系演替程度明显小于未受干扰的自然河流,1~6级支流各功能团的分布(P/%)梯度变化趋于平缓,仅捕食者数量分布与理论预测模式比较接近.各级支流相同取食功能团的优势类群各异,其种类的耐污能力随河流级别的增加总体呈上升趋势.同级支流各取食功能团的分布(P/%)比例存在季节性差异.图2表3参15     

Eco-environmental benefit assessment of China''''s South-North Water Transfer Scheme——the middle route project

IntroductionInordertoalleviateseverewatershortagesinnorthChina ,ChinesecentralgovernmenthavestartedtoimplementtheSouth NorthWaterTransferScheme(SNWT) ,whichwilltransferwaterfromYangtzeRiverbasininthesouthtoHuang Huai Hai(YellowRiver ,HuaiheRiverandHaiheRi…     

三江平原沼泽湿地底栖无脊椎动物群落特征

为探明现阶段三江平原沼泽湿地底栖无脊椎动物群落结构及物种多样性,于2017年春、夏、秋3个季节对6个样点开展了调查.共记录3门41科72种,以水生昆虫和腹足纲为主.平均密度为（139.68±29.13）ind./m²,季节上,底栖无脊椎动物密度表现为秋季>春季>夏季.三江平原沼泽湿地主要优势种具有一定的季节性变化,其中,西伯利亚盘螺Valvata sibirica为3个季节共有优势种.指示物种分析表明：春季指示种为Potamonectes sp.,夏季指示种为Lethocerus sp.、Gyraulus centrifugus、Erpobdellidae sp.;秋季指示种为Sgementina nitida.整体上,春季Shannon-Wiener多样性指数（H'）、均匀度指数（J）、Margalef丰富度指数（d_M）均比夏、秋季高.单因素方差分析表明,Shannon-Wiener多样性指数（F=1.480,p=0.259）、Margalef丰富度指数（F=0.056,p=0.946）、Pielou均匀性指数（F=2.038,p=0.165）均不存在季节性差异.     

Data classification and performance evaluation for the most commonly-used univariate alarm systems

Alarm systems are critically important for safe and efficient operations of industrial plants, but many industrial alarm systems are suffering from too many nuisance alarms. This paper proposes a method to classify normal and abnormal data segments and evaluate performance indices for the most commonly used univariate alarm systems. The proposed method consists of three steps. First, piece-wise linear representations are exploited in separating historical data samples of an analog process variable configured with alarms into data segments with same qualitative trends. Second, data segments are classified into normal, abnormal and unclassified conditions via a mean hypothesis test; a required assumption is that data segments in normal and abnormal conditions have different mean values being distinguishable from alarm thresholds. Third, based on the normal and abnormal data, performance indices of univariate alarm systems are calculated, including two newly formulated ones as the false alarm duration ratio and the missed alarm duration ratio. The effectiveness of the proposed method is illustrated by numerical and industrial examples.     

Macroinvertebrates As Bioindicators of Water Pollution in Streams Draining Dairy Farming Catchments

Runoff from intensive dairy farming systems can impair the quality of catchment waters, with potential ecological and human health implications. A water quality study was carried out in three streams in a predominantly dairy farming region, with the aim of assessing the effects of diffused- and point-sourced inputs on a number of water quality parameters and benthic macroinvertebrates. the results showed significant increases in streamwater biochemical oxygen demand (BOD), ammonium-nitrogen (NH₄-N) and molybdate reactive phosphorus (MRP) concentrations between the farm reaches. These changes in water quality appeared to be due largely to the point-sourced inputs from farmyards, and had a significant effect on the ability of the water to support a healthy and diverse community of invertebrates. the results also showed that concentrations of dissolved oxygen (DO) and ammonium in streamwater were the two most important parameters studied that were inversely related to the invertebrate scores.     

A link between ecological diversity indices and measures of biodiversity

The practice of environmental planning and protection frequently necessitates the quantification of ecological diversity. Traditional ‘ecological diversity indices’ are based on the abundances of species present. However, such indices are insensitive to taxonomic or similar differences. With equal species abundances they measure the species richness (species number) only. Conversely, so-called ‘biodiversity indices’ are based on species differences, but are insensitive to the abundance conditions. The quadratic entropy index is the only ecological diversity index, the value of which reflects both the differences ‘and’ abundances of the species. When a species list is given without abundance data, then, using the quadratic entropy index and postulating equal abundances, one gets the only biodiversity index derived from a traditional ecological index of diversity. Its extensive form is identical with the sum of differences or distances between the species present. This index trivially satisfies set monotonicity, an important property for biodiversity indices.