Organochlorine pesticides in the surface water and sediments from the Peacock River Drainage Basin in Xinjiang, China: a study of an arid zone in Central Asia

Fourteen surface water and nine surface sediment samples were collected from the Peacock River and analyzed for organochlorine pesticides (OCPs) by gas chromatograph?Celectron capture detector (GC-ECD). All the analyzed organochlorine pesticides, except o,p ^??-DDT, were detected in sediments from the Peacock River; but in the water samples, only ??-HCH, HCB, p,p ^??-DDD, and p,p ^??-DDT were detected at some sites. The ranges for total OCPs in the water and sediments were from N.D. to 195 ng l^???1 and from 1.36 to 24.60 ng g^???1, respectively. The only existing HCH isomer in the water, ??-HCH, suggested that the contamination by HCHs could be attributed to erosion of the weathered agricultural soils containing HCHs compounds. Composition analyses showed that no technical HCH, technical DDT, technical chlordanes, endosulfans, and HCB had been recently used in this region. However, there was new input of ??-HCH (lindane) into the Peacock River. The most probable source was water flowing from Bosten Lake and/or agricultural tailing water that was returned directly into the Peacock River. DDT compounds in the sediments may be derived mainly from DDT-treated aged and weathered agricultural soils, the degradation condition was aerobic and the main product was DDE. HCB in the sediment might be due to the input from Bosten Lake and the lake may act as an atmospheric deposition zone. There was no significant correlation between the concentrations of OCPs (including ??HCH, ??DDT, chlordanes, endosulfans, HCB and total OCPs) and the content of fine particles (<63 ??m). The concentrations of OCPs were affected by salinity.     

Vegetation response to hydrologic and geomorphic factors in an arid region of the Baja California Peninsula

Remotely sensed imageries were used to analyze the response of desert vegetation to physiographic factors and accumulated precipitation in drier and wetter years within a region of >16,500 km² sampled with 5,000 random pixels of 30 m. Vegetation development was indexed by the annual maximum values for greenness (SAVI) and canopy water content (NDII). Precipitation was interpolated from the 0.25° grid of the Tropical Rainfall Measurement Mission satellite-based estimates, showing a regional average of ～55 mm in the wetter year. The vegetation indices were only weakly related to total precipitation, often in a negative sense. Terrain factors that most often affected the vegetation indices, in multiple regression models, were Topographic Wetness Index, elevation, and slope gradient; these often had different signs for SAVI and for NDII. Models for NDII on intrusive igneous rocks gave better results than on extrusive igneous rocks. The strongest patterns in vegetation development were the contrast among Pacific coast, Cordillera, and Gulf coast subregions and the generally stronger results for NDII than SAVI.     

Changes in the area of inland lakes in arid regions of central Asia during the past 30 years

Inland lakes are major surface water resource in arid regions of Central Asia. The area changes in these lakes have been proved to be the results of regional climate changes and recent human activities. This study aimed at investigating the area variations of the nine major lakes in Central Asia over the last 30 years. Firstly, multi-temporal Landsat imagery in 1975, 1990, 1999, and 2007 were used to delineate lake extents automatically based on Normalized Difference Water Index (NDWI) threshold segmentation, then lake area variations were detailed in three decades and the mechanism of these changes was analyzed with meteorological data and hydrological data. The results indicated that the total surface areas of these nine lakes had decreased from 91,402.06 km² to 46,049.23 km² during 1975?C2007, accounting for 49.62% of their original area of 1975. Tail-end lakes in flat areas had shrunk dramatically as they were induced by both climate changes and human impacts, while alpine lakes remained relatively stable due to the small precipitation variations. With different water usage of river outlets, the variations of open lakes were more flexible than those of other two types. According to comprehensive analyses, different types of inland lakes presented different trends of area changes under the background of global warming effects in Central Asia, which showed that the increased human activities had broken the balance of water cycles in this region.     

灰色模型在确定关键污染因子中的应用

将灰色模型引入水环境质量评价中 ,通过对某个时间段内污染物原始监测数据的灰色处理 ,从动态演变中找出关键因子 ,客观地判定各污染因子所起的作用 ,并对各因子在下一个时间段的发展趋势作出判断 ,增加了评价的准确性。经过实例运用分析表明 ,该方法物理意义明确 ,简便易用     

Managed aquifer recharge by a check dam to improve the quality of fluoride-rich groundwater: a case study from southern India

In many regions around the globe, including India, degradation in the quality of groundwater is of great concern. The objective of this investigation is to determine the effect of recharge from a check dam on quality of groundwater in a region of Krishnagiri District of Tamil Nadu State, India. For this study, water samples from 15 wells were periodically obtained and analysed for major ions and fluoride concentrations. The amount of major ions present in groundwater was compared with the drinking water guideline values of the Bureau of Indian Standards. With respect to the sodium and fluoride concentrations, 38% of groundwater samples collected was not suitable for direct use as drinking water. Suitability of water for agricultural use was determined considering the electrical conductivity, sodium adsorption ratio, sodium percentage, permeability index, Wilcox and United States Salinity Laboratory diagrams. The influence of freshwater recharge from the dam is evident as the groundwater in wells nearer to the check dam was suitable for both irrigation and domestic purposes. However, the groundwater away from the dam had a high ionic composition. This study demonstrated that in other fluoride-affected areas, the concentration can be reduced by dilution with the construction of check dams as a measure of managed aquifer recharge.     

气相色谱法测定地下水中氯化苄

建立了气相色谱法测定地下水中氯化苄的方法。选用ＧＤＸ５０２大孔树脂或Ｃ１８小预处理柱吸附浓缩地下水中氯化苄,用苯洗脱,洗脱液注入色谱仪进行分析。方法回收率为８６４９８１％,变异系数＜８％。     

Dissolved antimony concentrations in contrasted watersheds: the importance of lithogenic origin

A large series of data on dissolved antimony concentrations (900 values) from the hydrological network of Canton Geneva, Switzerland, has been statistically analysed. Data were collected from 90 sampling sites over 12 years. The watercourses surveyed (178 km) accounted for 73% of the total network. Previous studies have classified these rivers as belonging to three clearly-differentiated lithogenic zones: Alps (rivers draining crystalline regions), Jura (rivers draining carbonate-rich zones) and Plain (rivers draining molasses derived from the Alps). Antimony concentrations in the different river waters have been found to be significantly dependent on the geological characteristics of the drainage basins (median values: 0.13, 0.08 and 0.16 microg L(-1) for Alps, Jura and Plain, respectively). For antimony, it is thus possible to define background levels of the element adapted to the lithogenic characteristics for a system of interest. Since establishing background levels is an unavoidable preliminary step in any study aiming to identify and evaluate the various sources of pollution, the behaviour described here has undeniable implications for environmental surveys.     

PSO和SVM混合算法确定太湖入湖河流水质主要影响因子

以影响太湖入湖河流水质的24个因子值为研究对象,将PSO算法与SVM算法相结合。PSO算法用于优化SVM算法的参数c和g,以利于快速、高效地确定c和g的全局最优值;SVM算法基于最优的c和g,分别以24,21,18,15,12,9和6个因子作为特征向量预测水质的污染程度。结果表明,当特征向量为9个影响因子时预测率最高。其参数c=18.56,g=1.35,对应的预测率为：全局预测率92.59%,重度污染水质预测率88.89%,轻度污染水质预测率94.45%。因此,通过PSO和SVM混合算法,可以确定影响太湖入湖河流水质的主要因子,利用这些主要因子对水质进行预测预警,不但可以节省时间,而且可以得到精确的结果。     

Utilization of polymerase chain reaction and selective media cultivation to identify Legionella in Taiwan spring water samples

In this study, we investigated the distribution of Legionella in sources of spring water and wastewater throughout Taiwan. Legionella were detected with culture method and PCR method from water samples, combined with molecular methods that allow the taxonomic identification of Legionella species. Factors associated with the distribution of Legionella including the physical?Cchemical and microbiological water quality characteristics were also measured. Legionella were detected in 18 of the 68 samples. Additionally, 16 of the 68 samples analyzed by polymerase chain reaction (PCR) and eight of the 68 samples evaluated using the culture method were found to be positive for Legionella. The Legionella species identified included Legionella pneumophila, unnamed Legionella genotypes, uncultured Legionella spp., and Legionella lytica. Legionella species were found in water with temperatures ranging from 10.0 to 50.6??C and with pH values ranging from 5.59 to 9.32. Significant differences (Mann?CWhitney U test, P?<?0.05) were observed in the presence/absence of Legionella in samples with different pH values when Legionella were detected by the culture method. The results of this survey confirmed that Legionella is ubiquitous in the water of spring recreational areas in Taiwan. Long-term investigations of the occurrence of Legionella in hot spring recreational areas throughout Taiwan are needed.     

Statistical approach for the assessment of water pollution around industrial areas: A case study from Patancheru,Medak district,India

Industrial effluents, surface waters, and subsurface groundwaters were sampled in and around the Patancheru industrial area of Nakkavagu basin, India and analysed. The parameters such as TDS, BOD, COD, and abundances of elements such as Cu, As, Se, F, Fe, are 5 to 10 times more than the permissible limits. These pollutants are contaminating the groundwaters at a faster rate than anticipated. A statistical approach is used to express the magnitude of pollution. Initially, correlation matrices of the major parameters and trace elements followed by factor analysis on them are presented to quantify the aspect of pollution. Factor 1 explaining 43.6% variance has positive loadings for variables TDS, BOD, COD, As, Cu, Se, SO ₄ ^–2 , and Cr, suggesting the factor is interpreted to be the Pollution or Migration of Pollutants. The same variables have negative loadings in the subsurface groundwaters suggesting that Factor 1 for these samples is a the depositionn or precipitation phenomenon. With a critical look at the Factor 1 of both surface and subsurface water samples it is indicated that pollutants migrated and became deposited in the environs of the Patancheru industrial area.