Combining multiple methods for provenance discrimination based on rare earth element geochemistry in lake sediment

Lingqing Wang; Xiaoxiao Han; Shiming Ding; Tao Liang; Yongyong Zhang; Jun Xiao; Linlin Dong; Haidong Zhang

doi:10.1016/j.scitotenv.2019.03.484

Combining multiple methods for provenance discrimination based on rare earth element geochemistry in lake sediment

Sci Total Environ. 2019 Jul 1:672:264-274. doi: 10.1016/j.scitotenv.2019.03.484. Epub 2019 Apr 2.

Authors

Lingqing Wang¹, Xiaoxiao Han², Shiming Ding³, Tao Liang², Yongyong Zhang², Jun Xiao⁴, Linlin Dong⁵, Haidong Zhang⁵

Affiliations

¹ Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: wanglq@igsnrr.ac.cn.
² Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
³ University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
⁴ State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi'an 710061, China. Electronic address: xiaojun@ieecas.cn.
⁵ Suzhou academy of agricultural sciences, Suzhou 215155, China.

PMID: 30959293
DOI: 10.1016/j.scitotenv.2019.03.484

Abstract

Geochemical properties of rare earth elements (REEs) have the potential to represent the provenance and depositional history of surface sediment in aquatic environments. In this study, both surface and core sediment samples were collected from Dongting Lake to investigate the distribution characteristics and source of REEs by combining the methodologies of geostatistics, positive matrix factorization (PMF) model, discriminant function (DF), and provenance index (PI) based on REEs geochemical parameters. The results indicated that the total REEs content in sediment samples ranged from 129.12 to 284.02 μg g^-1, with the average REEs content calculated to be 197.95 μg g^-1. Light REEs (LREEs) comprised >90% of the total REEs, indicating that there was an enrichment of LREEs in the sediment samples. The REEs of the surface sediment showed strong spatial variation, with relatively high values located in Eastern Dongting Lake and relatively lower levels in Western Dongting Lake. Moreover, the vertical distributions of ∑REEs, ∑LREEs and ∑HREEs at most sampling sites behaved similarly with rapid increase until about 6-8 cm, followed by a downward trend with some irregularities. The strong association between most REEs confirmed that they often have a positive correlation and co-existence in sediment. The PMF model revealed that most of the REEs in the surface sediment were derived from natural sources with some anthropogenic inputs also serving as contributing sources. The DF and PI results indicated that the REEs distribution pattern in the surface sediment of Dongting Lake was similar to that of the Yangtze River, suggesting that Yangtze River had been more of an influence on sediment loads than the upstream tributaries. This study highlights the broader applicability of the REEs tracing method in sediment transport processes and can provide new knowledge regarding source apportionment analysis of sediment-related contaminants in aquatic environments.

Keywords: Discriminant function; Lake; Positive matrix factorization; Provenance index; Rare earth element; Sediment.