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中国临汾水库沉积物磁性与化学参数揭示的大气污染历史

Atmospheric pollution history at Linfen (China) uncovered by magnetic and chemical parameters of sediments from a water reservoir.

作者信息

Ma Mingming, Hu Shouyun, Cao Liwan, Appel Erwin, Wang Longsheng

机构信息

State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; 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.

出版信息

Environ Pollut. 2015 Sep;204:161-72. doi: 10.1016/j.envpol.2015.04.028. Epub 2015 May 14.

DOI:10.1016/j.envpol.2015.04.028
PMID:25969376
Abstract

We studied magnetic and chemical parameters of sediments from sediments of a water reservoir at Linfen (China) in order to quantitatively reconstruct the atmospheric pollution history in this region. The results show that the main magnetic phases are magnetite and maghemite originating from the surrounding catchment and from anthropogenic activities, and there is a significant positive relationship between magnetic concentration parameters and heavy metals concentrations, indicating that magnetic proxies can be used to monitor the anthropogenic pollution. In order to uncover the atmospheric pollution history, we combined the known events of environmental improvement with variations of magnetic susceptibility (χ) and heavy metals along the cores to obtain a detailed chronological framework. In addition, air comprehensive pollution index (ACPI) was reconstructed from regression equation among magnetic and chemical parameters as well as atmospheric monitoring data. Based on these results, the atmospheric pollution history was successfully reconstructed.

摘要

我们研究了中国临汾某水库沉积物的磁性和化学参数,以便定量重建该地区的大气污染历史。结果表明,主要磁性相为磁铁矿和磁赤铁矿,它们源自周边集水区和人为活动,磁性浓度参数与重金属浓度之间存在显著正相关,这表明磁性指标可用于监测人为污染。为了揭示大气污染历史,我们将已知的环境改善事件与岩芯中磁化率(χ)和重金属的变化相结合,以获得详细的年代框架。此外,根据磁性和化学参数以及大气监测数据之间的回归方程重建了空气综合污染指数(ACPI)。基于这些结果,成功重建了大气污染历史。

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