石油类测定质量自控方法探讨

探讨了水中石油类测定中自控标准样品的配制方法,按1∶1∶1的比例配制正十六烷、姥鲛烷和甲苯混合标准溶液,对国家标准样品的测定值在保证值范围内。配制的20.0 mg/L和1.00 mg/L高、低两种质量浓度的混合标准溶液,连续7 d随水样同时测定的相对误差≤7.0%,RSD在1.3%～6.7%范围。     

江苏省太湖流域水环境自动监控系统技术框架构建研究

为全面提升江苏省水环境的监控预警能力,我省在太湖流域相关市县建立了覆盖省市交界断面、出入湖口门、饮用水源地的全方位自动监控网络,为相关自动监控系统的技术框架构建提供了重要参考依据,弥补了现行环境监测体系的不足,为太湖流域的监控预警、生态补偿、流域考核等工作提供了重要参考。     

丹江口库区及其上游流域水质污染特征及评价

根据丹江口库区及其上游河流5个区域42个断面2012-2013年的水质监测数据,采用主成分分析法确定主要污染因子及权重,对不同流域的水质进行综合评价。第一主成分包括总氮、溶解氧、五日生化需氧量、总磷、氨氮、高锰酸盐指数,第二主成分为氟化物、粪大肠菌群,第三主成分为化学需氧量;其权重分别为5．022,2．256,1．508。评价结果表明,湖北十堰市和丹江口市流域水环境污染相对较重,其次为河南南阳市、陕西商洛市、陕西安康市以及陕西汉中市流域。     

国家地表水水质自动监测网的建设与运行

总结了中国地表水水质自动监测网的建设运行与应用现状,分析了水站目前在运行管理、数据质量保证和质量控制中存在的问题,并就今后利用水质自动监测数据进行综合分析以及保障水质自动监测的可持续发展提出了意见和建议。     

建立水质自动监测系统的思考

结合章郭水质自动监测系统的可行性研究,在建立水质自动监测系统过程中对监测站位的选取、监测项目的选择、水质自动监测系统的组成、数据的采集与处理、系统的维护及管理、存在的问题等方面进行探讨,水质自动监测系统的建设可以弥补水质监测的不足,同时为实施总量控制及环境管理提供了可靠的依据。     

生态工程治理玄武湖水污染效果的监测与评价

选取总磷、总氮、叶绿素a、浮游生物、浮游植物等多项环境监测指标,对利用生态工程治疗玄武湖水环境污染的效果进行了环境监测与评价。指出生态工程治理玄武湖水环境污染效果显著,经过治理使湖水中生物多样性大大增加,浮游植物大幅减少,湖水透明度增加,总磷、总氮等主要指标大幅下降,生态工程区中的水环境已从高度富营养化降到中度富营养化。     

Genotoxicity evaluation of water soil leachates by Ames test, comet assay, and preliminary Tradescantia micronucleus assay

Combining genotoxicity/mutagenicity tests and physico-chemical methodologies can be useful for determining the potential genotoxic contaminants in soil samples. The aim of our study was to evaluate the genotoxicity of soil by applying an integrated physico-chemical-biological approach. Soil samples were collected at six sampling points in a Slovenian industrial and agricultural region where contamination by heavy metals and sulphur dioxide (SO₂) are primarily caused by a nearby power plant. The in vitro alkaline version of the comet assay on water soil leachates was performed with Caco-2 and HepG2 cells. A parallel genotoxicity evaluation of the samples was performed by Ames test using Salmonella typhimurium and the Tradescantia micronucleus test. Pedological analyses, heavy metal content determination, and different physico-chemical analyses, were also performed utilizing standard methodology. Water leachates of soil samples were prepared according to standard methods. Since only a battery of biotests with prokaryotic and eukaryotic organisms or cells can accurately estimate the effects of (geno)toxicants in soil samples and water soil leachates, a combination of three bioassays, with cells or organisms belonging to different trophic levels, was used. Genotoxicity of all six water soil leachates was proven by the comet assay on both human cell lines, however no positive results were detected by bacterial assay, Ames test. The Tradescantia micronucleus assay showed increase in micronuclei formation for three samples. According to these results we can assume that the comet assay was the most sensitive assay, followed by the micronucleus test. The Ames test does not appear to be sensitive enough for water soil leachates genotoxicity evaluations where heavy metal contamination is anticipated.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Multivariate analysis of drinking water quality parameters in Bhopal, India

Pollution of water bodies is one of the areas of major concern to environmentalists. Water quality is an index of health and well being of a society. Industrialization, urbanization and modern agriculture practices have direct impact on the water resources. These factors influence the water resources quantitatively and qualitatively. The study area selected were the Upper lake and Kolar reservoir of Bhopal, the state capital of Madhya Pradesh, India. The Upper lake and Kolar reservoir both are the important sources of potable water supply for the Bhopal city. The physico–chemical parameters like temperature, pH, turbidity, total hardness, alkalinity, BOD, COD, Chloride, nitrate and phosphate were studied to ascertain the drinking water quality.     

Application and evaluation of kriging and cokriging methods on groundwater depth mapping

Groundwater and water resources management play a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying some techniques that can reveal the critical and hot conditions of water resources seem necessary. In this study, kriging and cokriging methods were evaluated for mapping the groundwater depth across a plain in which has experienced different climatic conditions (dry, wet, and normal) and consequently high variations in groundwater depth in a 12 year led in maximum, minimum, and mean depths. During this period groundwater depth has considerable fluctuations. Results obtained from geostatistical analysis showed that groundwater depth varies spatially in different climatic conditions. Furthermore, the calculated RMSE showed that cokriging approach was more accurate than kriging in mapping the groundwater depth though there was not a distinct difference. As a whole, kriging underestimated the real groundwater depth for dry, wet, and normal conditions by 5.5, 2.2, and 5.3%, while cokriging underestimations were 3.3, 2, and 2.2%, respectively; which showed the unbiasedness in estimations. Results implied that in the study area farming and cultivation in dry conditions needs more attention due to higher variability in groundwater depth in short distances compared to the other climate conditions. It is believed that geostatistical approaches are reliable tools for water resources managers and water authorities to allocate groundwater resources in different environmental conditions.