Soil contamination of heavy metals in the Katedan Industrial Development Area, Hyderabad, India

Studies on quantitative soil contamination due to heavy metals were carried out in Katedan Industrial Development Area (KIDA), south of Hyderabad, Andhra Pradesh, India under the Indo-Norwegian Institutional Cooperation Programme. The study area falls under a semi-arid type of climate and consists of granites and pegmatite of igneous origin belonging to the Archaean age. There are about 300 industries dealing with dyeing, edible oil production, battery manufacturing, metal plating, chemicals, etc. Most of the industries discharge their untreated effluents either on open land or into ditches. Solid waste from industries is randomly dumped along roads and open grounds. Soil samples were collected throughout the industrial area and from downstream residential areas and were analysed by X-ray Fluorescence Spectrometer for fourteen trace metals and ten major oxides. The analytical data shows very high concentrations of lead, chromium, nickel, zinc, arsenic and cadmium through out the industrial area. The random dumping of hazardous waste in the industrial area could be the main cause of the soil contamination spreading by rainwater and wind. In the residential areas the local dumping is expected to be the main source as it is difficult to foresee that rain and wind can transport the contaminants from the industrial area. If emission to air by the smokestacks is significant, this may contribute to considerable spreading of contaminants like As, Cd and Pb throughout the area. A comparison of the results with the Canadian Soil Quality Guidelines (SQGL) show that most of the industrial area is heavily contaminated by As, Pb and Zn and local areas by Cr, Cu and Ni. The residential area is also contaminated by As and some small areas by Cr, Cu, Pb and Zn. The Cd contamination is detected over large area but it is not exceeding the SQGL value. Natural background values of As and Cr exceed the SQGL values and contribute significantly to the contamination in the residential area. However, the availability is considerably less than anthropogenic contaminants and must therefore be assessed differently. The pre- and post-monsoon sampling over two hydrological cycles in 2002 and 2003 indicate that the As, Cd and Pb contaminants are more mobile and may expect to reach the groundwater. The other contaminants seem to be much more stable. The contamination is especially serious in the industrial area as it is housing a large permanent residing population. The study not only aims at determining the natural background levels of trace elements as a guide for future pollution monitoring but also focuses on the pollution vulnerability of the watershed. A plan of action for remediation is recommended.     

南京市冬季大气颗粒态汞的分布特征

采集了南京市2012年冬季4个功能区的PM2．5、PM10、TSP样品,对不同粒径大气颗粒物中的颗粒态汞测试。结果表明,南京冬季大气颗粒物TSP中汞的质量浓度为49．26 pg/m3～257．14 pg/m3,平均质量浓度为161．27 pg/m3;PM10中汞的质量浓度为44．82 pg/m3～228．29 pg/m3,平均质量浓度为147．38 pg/m3;PM2．5中汞的质量浓度为35．98 pg/m3～178．58 pg/m3,平均质量浓度为104．10 pg/m3。不同功能区大气颗粒态汞质量浓度的分布趋势为：交通综合区＞旅游区＞住宿综合区＞商业区。大气颗粒态汞60％以上存在于可吸入肺的PM2．5中,细颗粒物富集汞的能力比粗颗粒物强。     

Heavy metal distribution and speciation in the Northern Adriatic Sea

In the present study the concentrations of cobalt, copper, iron, manganese, zinc were analysed and the speciation of copper and zinc performed, with a summer and winter sampling, for two areas in the Northern Adriatic Sea and crossing at the farthest zones of the Po river-sea water interface. Results show that when salinity increases the concentrations of all investigated metals (with the exception of cobalt) present some degree of biogeochemical cycling. Copper is the element whose dissolved phase has the highest importance in metal transport across the salinity gradient. Results of speciation analysis demonstrate that the presence of excess amounts (5-8 fold) of unbound ligands confers a buffering capacity for potential inputs of dissolved metals into the Northern Adriatic Sea. The speciation of both copper and zinc in the dissolved phase was dominated by organic complexation.     

University of Benin water supply system: Microbiological and physico-chemical assessments

The microbiological and physico-chemical characteristics of the drinking water supplied by the Central Borehole at the University of Benin, Ugbowo Campus were investigated. The investigation entailed assessment of the pH, turbidity, total suspended solids, total dissolved solids, dissolved oxygen, temperature, salinity, conductivity, nitrate, nitrite, phosphate, sulphate, chloride, N-nitroso compounds, cadmium, chromium, nickel, lead, zinc, manganese, iron, coliform count, BOD₅ and COD of the water at the Central Borehole and at ten residential quarters. The assessment indicated that the water was fit for drinking and other domestic applications. Results were also compared with WHO, EU and Nigeria FEPA standards. The results showed that the pH values of the water (5.01–5.86) and total coliform count (1–2/100 ml) expressed as MPN were outside the limits set by the WHO, EU and FEPA. The data also showed that the other water quality parameters assessed were within WHO, EU and FEPA permissible limits. The results of ANOVA showed that significant changes occurred during distribution.     

鄱阳湖典型湿地沉水植物的分布格局及其水环境影响因子

沉水植物是湖泊湿地生态系统中关键组分,调查研究沉水植物分布格局及其水环境影响因子,对于沉水植被的恢复与重建具有重要的指导意义。2013年5月初期分别对鄱阳湖典型湿地区域中有沉水植物的25个样地进行群落结构调查,采用系统取样方法对沉水植物进行调查采样并监测水环境因子,在野外调查的基础上运用GIS软件制作鄱阳湖典型区域沉水植物的生物量分布图,并采用主成分分析(PCA)和典范对应分析(CCA)方法分析其主要影响因子。结果表明:鄱阳湖湿地沉水植物以苦草(Vallisneria natans)为广布种,其中蚌湖及白沙湖以黑藻(Hydrilla verticillata)为优势种,白沙洲及乐安河龙口段以苦草为优势种,伴生种主要有金鱼藻(Ceratophyllum demersum)、马来眼子菜(Potamogeton malaianus)、菹草(P.crispus)、小茨藻(Najas minor)、大茨藻(N.marina)、刺苦草(V.spinulosa)和水车前(Ottelia alismoides)等。采用双向指示种分析法将研究区沉水植物分为6个群落;5月初大部分沉水植物尚处于生长季初期,生物量相对较低,仅菹草的生物量较大;沉水植物与浮叶植物共存现象明显。主成分分析(PCA)结果显示,第一主成分中水深、总磷和溶解氧等因子的系数值较大,第二主成分中pH值、化学需氧量和水体透明度等因子的系数值较大,是影响沉水植物分布的关键因子;典范对应分析(CCA)结果显示,水深、总磷和总氮对苦草和黑藻的影响显著,水体透明度是马来眼子菜的主要影响因子。     

浅谈我国冰雹的分布规律及其保险对策

本文从冰雹灾害的分布规律着手,研究我国雹灾对策形式之一——雹灾保险,在对世界各国雹灾保险借鉴的基础上,选择我国雹灾保险的模式,建立适合我国国情的雹灾保险。     

Extension of twoCaulerpa species along the Tunisian coast

Two species of the green alga genusCaulerpa are considered as invasive in Tunisia:Caulerpa racemosa andC. taxifolia. C. racemosa is found in a many new localities at the central and southern Tunisian coast, and even in the North of the country in colder water. These new observations lead to the hypothesis of the multiplicity of the origins of the introduction of the species and suggest possible invasive potentialities. The general thallus, and more particularly the number, the shape as well as the arrangement of ramelli on fronds allowed us to identify four morphologically different groups. These groups could be either different systematic entities or polymorphic variations of the same taxon due to different ecological conditions.Caulerpa taxifolia was observed for the first time in Tunisia at the roadstead of Sousse in the beginning of the year 2000. It is recognized as identical to that found in the other Mediterranean localities (GenBank number AJ228960). Up to the end of March 2000, a submarine prospecting campaign revealed an affected area of about 350 ha in front of 2 km of coast. Colonies ofCaulerpa taxifolia disseminating in this area appear in isolated spots. form, In the growing stage, they form surfaces varying between 0.5 to 6 m² and located 20 to 100 m from each other. The total covered surface was estimated to be between 0.5 and 1 ha.     

锶—89在珍珠岩中吸附的研究

研究了不同粒径的珍珠岩对＾８９Ｓｒ的吸附。结果表明，珍珠岩对＾８９Ｓｒ具有较强的吸附能力，饱和吸附率大于９５％；通过振荡能加速珍珠岩对＾８９Ｓｒ的吸附；珍珠岩对＾８９Ｓｒ的吸附率与时间关系由多项指数描述；不同粒径的珍珠岩对＾８９Ｓｒ的吸附率没有明显差异。     

The distribution,metabolism and toxicity of 14c-DDT in model aquarium tanks with fish and sediment simulating a tropical marine environment

Studies conducted on the distribution, fate and metabolism of DDT in a model ecosystem simulating a tropical marine environment of fish, Gobious nudiceps, Lethrinus harak, Gobious keinesis, Gobious nebulosis and white shrimp (Panaeus setiferus), show that DDT concentration in the water decreases rapidly within the first 24?h. Rapid accumulation of the pesticide in the biota also reaches a maximum level in 24?h before gradually declining. The bioaccumulation factors calculated for the fish species (G. keinesis) and white shrimp (P. Setiferus) were 270 and 351, respectively, after 24?h. There was a steady build up of DDT residues in the sediment during the first 24?h which continued to a maximum concentration of 6.66?ng/g in the seawater/fish/sediment ecosystem after 3 weeks and 5.27?ng/g in the seawater/shrimps/sediment ecosystem after 2.7 days. The depuration of the accumulated pesticide was slow with only 54% lost in G. nudiceps within 3 days of exposure in fresh sea water. By contrast, depuration was fast in the white shrimp, which lost 97% of the accumulated pesticide under the same conditions. DDT was found to be toxic to two of the fish species (G. nebulosis and L. harak) and to white shrimp, and the degree of toxicity was dependent on the particular species. The 24?h LC₅₀ at room temperature for the fish species G. nebulosis and white shrimp was found to be 0.011 and 0.116?mg/kg, respectively. These levels are comparable to the ones recorded for the temperate organisms. Degradation of DDT to its primary metabolites, DDE and DDD, was found in all the compartments of the ecosystem with DDE being the major metabolite in the fish, shrimps and sediment, while in seawater, DDD dominated as the major metabolite.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.