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Statistical Modeling of Global Geogenic Fluoride Contamination in Groundwaters

机译:地下水中全球地质氟污染的统计模型

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摘要

The use of groundwater with high fluoride concentrations poses a health threat to millions of people around the world. This study aims at providing a global overview of potentially fluoride-rich groundwaters by modeling fluoride concentration. A large database of worldwide fluoride concentrations as well as available information on related environmental factors such as soil properties, geological settings, and climatic and topographical information on a global scale have all been used in the model. The modeling approach combines geochemical knowledge with statistical methods to devise a rule-based statistical procedure, which divides the world into 8 different "process regions". For each region a separate predictive model was constructed. The end result is a global probability map of fluoride concentration in the groundwater. Comparisons of the modeled and measured data indicate that 60-70% of the fluoride variation could be explained by the models in six process regions, while in two process regions only 30% of the variation in the measured data was explained. Furthermore, the global probability map corresponded well with fluorotic areas described in the international literature. Although the probability map should not replace fluoride testing, it can give a first indication of possible contamination and thus may support the planning process of new drinking water projects.
机译:使用氟化物浓度高的地下水对全球数百万人构成健康威胁。本研究旨在通过对氟化物浓度进行建模来提供潜在富氟化物地下水的全球概况。该模型使用了一个庞大的全球氟化物浓度数据库以及有关环境因素(如土壤特性,地质环境以及全球范围内的气候和地形信息)的可用信息。建模方法将地球化学知识与统计方法相结合,以设计基于规则的统计程序,该程序将世界划分为8个不同的“过程区域”。对于每个区域,构建单独的预测模型。最终结果是地下水中氟化物浓度的全球概率图。建模数据和测量数据的比较表明,模型可以在六个过程区域中解释60-70%的氟化物变化,而在两个过程区域中,仅解释了测量数据中30%的变化。此外,全球概率图与国际文献中描述的氟区域非常吻合。尽管概率图不能替代氟化物测试,但它可以初步表明可能的污染,因此可以支持新饮用水项目的规划过程。

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