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91.
超临界二氧化碳萃取-GC/MS测定土壤中的多环芳烃 总被引:10,自引:2,他引:10
本文开发了一种采用超临界二氧化碳萃取土壤中多环芳烃、不须经过纯化步骤,直接可用于GC/MS分析的简便、高效的方法。本实验中超临界革取的流体是二氧化碳,改善剂是5%的二氯甲烷/甲醇,萃取温度为120℃、压力为34MPa。GC/MS分析时除了采用外标外,还加入了6种同位素PAHs内标以校正各段PAHs的响应因子。采用本方法成功地测定了我国未开垦森林土壤中的PAHs。 相似文献
92.
在线自动监测仪与实验室国标方法测定地表水中总氮的比对分析 总被引:2,自引:2,他引:2
随着监测技术的发展,地表水中越来越多的污染物可采用自动监测仪器实现实时监测。采用自动监测与实验室国标方法测定地表水中总氮的结果是否可比以及造成差异的原因,文章根据实际样品比对实验对此进行了探讨。 相似文献
93.
离子色谱分析中的几个问题探讨 总被引:7,自引:0,他引:7
在掌握离子色谱技术最新发展动态的基础上,对离子色谱的新进展、前处理新技术、常用的改善分离度方法、若干注意事项、常遇到的问题等进行了分析探讨,以期用离子色谱技术更多更好地解决实际问题. 相似文献
94.
连续采样与五日法采样效果及费用的对比分析 总被引:2,自引:0,他引:2
通过对连续采样与五日法采样五种方法监测结果及所需费用的比较,得出连续采样方法监测结果更具有代表性,合理性,一次性投资大,但运行费用并不高的结论。 相似文献
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97.
利用EXCEL强大的数据处理功能,可以方便地对精密度—偏性分析质控数据进行处理,具有较高的推广价值。 相似文献
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Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO4, and NO3 concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models. 相似文献
100.
Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong 总被引:4,自引:0,他引:4
As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NOx and NO2 are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NOx and NO2 concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NOx and NO2 concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods. 相似文献