Truu Jaak, Heinaru Eeva, Talpsep Ene, Heinaru Ain
Institute of Molecular and Cell Biology, University of Tartu, 23 Riia Str., EE-51010 Tartu, Estonia.
Environ Sci Pollut Res Int. 2002;Spec No 1:8-14. doi: 10.1007/BF02987419.
The oil-shale industry has created serious pollution problems in northeastern Estonia. Untreated, phenol-rich leachate from semi-coke mounds formed as a by-product of oil-shale processing is discharged into the Baltic Sea via channels and rivers. An exploratory analysis of water chemical and microbiological data sets from the low-flow period was carried out using different multivariate analysis techniques. Principal component analysis allowed us to distinguish different locations in the river system. The riverine microbial community response to water chemical parameters was assessed by co-inertia analysis. Water pH, COD and total nitrogen were negatively related to the number of biodegradative bacteria, while oxygen concentration promoted the abundance of these bacteria. The results demonstrate the utility of multivariate statistical techniques as tools for estimating the magnitude and extent of pollution based on river water chemical and microbiological parameters. An evaluation of river chemical and microbiological data suggests that the ambient natural attenuation mechanisms only partly eliminate pollutants from river water, and that a sufficient reduction of more recalcitrant compounds could be achieved through the reduction of wastewater discharge from the oil-shale chemical industry into the rivers.
油页岩工业在爱沙尼亚东北部造成了严重的污染问题。未经处理的、富含苯酚的渗滤液来自油页岩加工副产品形成的半焦堆,通过渠道和河流排入波罗的海。利用不同的多元分析技术,对枯水期的水化学和微生物数据集进行了探索性分析。主成分分析使我们能够区分河流系统中的不同位置。通过共惯性分析评估了河流微生物群落对水化学参数的响应。水的pH值、化学需氧量和总氮与生物降解细菌的数量呈负相关,而氧气浓度则促进了这些细菌的丰度。结果表明,多元统计技术作为基于河水化学和微生物参数估算污染程度和范围的工具是有用的。对河流化学和微生物数据的评估表明,环境自然衰减机制只能部分消除河水中的污染物,通过减少油页岩化学工业向河流排放废水,可以充分减少更多难降解化合物的排放。