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.     

A new method of predicting of gas chromatographic retention indices for polychlorinated dibenzofurans (PCDFs)

A new method has been developed to describe the quantitative relationship between molecular structures of PCDFs and their gas chromatographic retention indices on a 30-m fused silica column coated with DB-5 stationary phase. The regression equation is derived with a multiple correlation coefficient greater than 0.9995. The highest residual is 20 index units. The standard deviation is less than 7 index units. Using this regression equation, the retention indices of PCDFs for which data is not available have also been predicted.     

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。     

QSAR计算中的分子连接性指数法

本文介绍了分子连接性指数法和原理及各阶指数的计算方法，以及在ＱＳＡＲ计算中的应用实例，并对特殊连接性指数的用法作了分析。     

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…     

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.     

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.     

1961—2010年新疆生长季节指数时空变化特征及其农业响应

在定义生长季节长度(GSL)、生长季节开始时间(LSF)以及生长季节结束时间(FFF)三个生长季节指数的基础上,采用模糊聚类、稳健回归及Mann-Kendall非参数检验等方法分析新疆1961—2010年生长季节指数时空变化特征,并针对作物生长季节指数变化对区域农业生产的影响进行了深入探讨。结果表明:新疆20世纪90年代中期,GSL变化幅度很大,低纬地区生长季节受低温影响较小,而随纬度上升,中高纬地区生长季节受低温影响越大。生长季节长度的变化与秋季低温(生长季节结束时间)变化情况紧密相连,全疆生长季节长度在80%的保证率下,较多年平均生长季节长度缩短5~14 d。生长季节长度的延长,会导致净初级生产力以及年蒸散发总量上升,继而影响水文、生态系统以及生物地球化学过程。