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641.
The main objective of this study was to investigate occurrence of polycyclic aromatic hydrocarbons (PAHs) in the sources of the drinking water supply of Hong Kong. The main emphasis was on the Dongjiang River in mainland China which is the major source, supplying 80% of the total consumption in Hong Kong (the remaining 20% is obtained from rain water). Sediments were collected from four sites along the Dongjiang River and four reservoirs in Hong Kong during both the dry and wet weather seasons. The concentrations of total PAHs in the sediments ranged between 36 and 539 microg/kg dry wt. The lower levels were detected at the upstream site on the Dongjiang River and at the reservoirs in Hong Kong (44-85 microg/kg dry wt), while the mid- and downstream sites on the Dongjiang River were more polluted (588-658 microg/kg dry wt). Examination of the PAH profiles revealed that the mid- and downstream sections of the Dongjiang River contained high percentages of 4,5,6-ring PAHs, similar to the amounts of atmospheric particulate matter and road dust collected during the dry weather season from the Pearl River Delta region as reported in the literature. Seasonal changes were revealed in the reservoirs of Hong Kong, with higher PAH levels in the wet weather season than in the dry weather season. For those reservoirs in Hong Kong that store water from the Dongjiang River, a distinct seasonal pattern was also observed, namely, that under dry weather season conditions the PAHs found in the sediments were primarily from petrogenic source, while under wet weather season conditions they were from pyrolytic sources. No such pattern was detected in the reservoirs which stored only rain water. 相似文献
642.
ICP-MS法同时测定地表水中18种金属元素 总被引:4,自引:1,他引:3
以115In-103Rh为双内标校正系统,采用电感耦合等离子体质谱法同时测定地表水中铜、锌、硒、砷、汞、镉、铅、铁、锰、钼、钴、铍、锑、镍、钡、钒、钛、铊等18种金属元素,优化了测量同位素、内标元素等试验条件。18种金属元素在0μg/L~100μg/L范围内线性良好,检出限为0.006μg/L~0.123μg/L,标准样品的测定值均在保证值范围内,平行测定的RSD为1.7%~4.2%,实际水样加标回收率为89.0%~100%。 相似文献
643.
我国水环境有机物分析前处理技术 总被引:1,自引:0,他引:1
介绍了我国水环境有机物分析中常用的前处理技术,包括液液萃取、树脂吸附、固相萃取、固相微萃取、液膜萃取、半透膜被动采样、顶空、吹扫-捕集等,归纳了各种方法的原理、应用及优缺点,并对环境中有机污染物前处理技术的发展方向进行了展望。 相似文献
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Dongqi Wang Yanling He Jidong Liang Pei Liu Pengyu Zhuang 《Environmental monitoring and assessment》2013,185(2):1041-1053
To study the status and source of aluminum (Al) contamination, a total of 21 sampling sites along six rivers near Xi’an City (Shaanxi province, China) were investigated during 2008–2010. The results indicated that the average concentration of total Al (Alt) in the six rivers increased by 1.6 times from 2008 to 2010. The spatial distribution of Alt concentrations in the rivers near Xi’an City was significantly different, ranged from 367 μg/L (Bahe River) to 1,978 μg/L (Taiping River). The Alt concentration was highest near an industrial area for pulp and paper-making (2,773 μg/L), where the Al level greatly exceeded the water quality criteria of both the USA (Criterion Continuous Concentration, 87 μg/L) and Canada (100 μg/L). The average concentration of inorganic monometric aluminum (Alim) was 72 μg/L which would pose threats to fishes and other aquatic lives in the rivers. The concentrations of exchangeable Al (Alex) in the sediment of the Taiping River sampled were relatively high, making it to be an alternative explanation of increasing Al concentrations in the rivers near Xi’an City. Furthermore, an increasing Al level has been detected in the upstream watershed near Xi’an City in recent years, which might indicate another notable pollution source of Al. 相似文献
647.
Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China 总被引:2,自引:0,他引:2
Xiaohu Wen Jing Fang Meina Diao Chuanqi Zhang 《Environmental monitoring and assessment》2013,185(5):4361-4371
Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl?), calcium (Ca2+), total alkalinity, total hardness, nitrate nitrogen (NO3-N), and ammonical nitrogen (NH4-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO3-N, NH4-N, and Ca2+. Cl? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters. 相似文献
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采用碱片-离子色谱法测定空气的硫酸盐化速率,方法在硫酸盐质量浓度为1.00~20.0 mg/L范围内线性良好(r≥0.999 0);碱片剪碎或不剪碎对空白碱片中硫酸根离子质量浓度的测定无明显影响,且高低两种加标浓度的回收率均在80.0%~120%之间;对于碱片实际样品,碱片剪碎更有利于硫酸根离子的快速溶出;随浸泡时间的延长,碱片中溶出的硫酸根离子质量浓度呈上升趋势,7 h硫酸根离子基本溶出完全,从保证结果质量和节省时间的角度考虑,确定最佳浸泡时间为3.5 h,建议碱片全部采取剪碎处理。 相似文献