Nakamura Kengo, Kawabe Yoshishige, Komai Takeshi
Graduate School of Environmental Sciences, Tohoku University, 6-6-20 Aoba, Aramaki, Aoba-ku, Sendai, 980-8579, Japan.
National Institute of Advanced Industrial Science and Technology, Institute for Geo-Resources and Environments, Geo-Environment Analysis and Evaluation Research Group, 1-1-1 Higashi, Tsukuba, 305-8567, Japan.
Heliyon. 2021 May 5;7(5):e06927. doi: 10.1016/j.heliyon.2021.e06927. eCollection 2021 May.
River sediments have the effect of aggregating geochemical environmental information, such as that related to geological and artificial pollution resulting from mine closure. This information comprises high-dimensional data and is related to the distribution and quantities of elements in river sediments. However, accessing and interpreting this geochemical information can be difficult. This study employed a data-driven analysis that can be mathematically and statistically reduced in dimension. Using high-dimensional geochemical and environmental information on river sediments, this study evaluated the environmental impact of closed mines. Sample for analysis were collected from three rivers. There are differences in the existence of mines and mine wastewater treatment methods in this river. A total of 33 elements were measured in river sediments. Frequency distribution analysis and Principal component analysis revealed that the elements had unique distribution and frequency characteristics in each river catchment. Four environmental factors could be extracted from the relationship of elements due to lower dimension. PC1 was influenced by the land use in the river area. PC2 captured the geological background. PC3 captured the mixing-diluting effect that occurs in rivers. PC4 effectively captured the effects of domestic wastewater and the effects of closed mines. The effects of the closed mines could be confirmed using the PC4 score for the Okawa River and the Akagawa River. By examining the elemental relationships obtained using these mathematical methods, it is possible to infer the effect of geological features and mines on sediment physiochemistry using existing data on river sediments.
河流沉积物具有聚集地球化学环境信息的作用，比如与矿山关闭导致的地质和人为污染相关的信息。这些信息包含高维数据，且与河流沉积物中元素的分布和含量有关。然而，获取和解读这些地球化学信息可能具有难度。本研究采用了一种可在数学和统计层面进行降维的数据驱动分析方法。利用河流沉积物的高维地球化学和环境信息，本研究评估了关闭矿山的环境影响。分析样本取自三条河流。这些河流在矿山存在情况及矿山废水处理方法上存在差异。共对河流沉积物中的33种元素进行了测量。频率分布分析和主成分分析表明，各元素在每个流域具有独特的分布和频率特征。由于维度较低，从元素关系中可提取出四个环境因素。主成分1受河流区域土地利用的影响。主成分2反映了地质背景。主成分3体现了河流中发生的混合稀释效应。主成分4有效捕捉了生活污水的影响以及关闭矿山的影响。利用小川河和赤川河的主成分4得分可证实关闭矿山的影响。通过研究使用这些数学方法获得的元素关系，有可能利用河流沉积物的现有数据推断地质特征和矿山对沉积物物理化学性质的影响。
