Literature DB >> 31026698

Concentration decline in response to source shift of trace metals in Elbe River, Germany: A long-term trend analysis during 1998-2016.

Zhenyu Wang1, Pei Hua2, Ruifei Li3, Yun Bai4, Gongduan Fan5, Peng Wang6, Bill X Hu6, Jin Zhang7, Peter Krebs3.   

Abstract

Monitoring spatial and temporal chemical status of water bodies is crucial to assist environmental policy, identify the chemical fingerprints, and further reduce the source orientated pollutants. Elbe River is one of the major rivers affected by anthropogenic activities in vicinity countries. This study assessed the spatiotemporal changes in response to source shift of Cd, Cu, Ni, Pb, and Zn in the suspended particulate matter (SPM) at upstream, midstream, and downstream of the Elbe River reach in Saxony state, Germany. The average contents of trace metals in SPM was found in the order of Zn (676 mg/kg) » Pb (79 mg/kg) > Cu (74 mg/kg) > Ni (48 mg/kg) » Cd (3.2 mg/kg). According to the Mann-Kendall trend test, Cd, Cu, Pb, and Zn showed significant declines over 1998-2016. The results of source apportionment indicate industrial, urban, natural, and historical mining sources influencing the metal contents in the Elbe River of Saxony. The contributions of industrial and urban pollution decreased by 58.2% from 1998 to 2007 to 2008-2016. The contribution of the natural source was steady over the last two decades.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Long-term trend; Positive matrix factorization; Source apportionment; Trace metals

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Year:  2019        PMID: 31026698     DOI: 10.1016/j.envpol.2019.04.062

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  2 in total

1.  Influence of surface properties and antecedent environmental conditions on particulate-associated metals in surface runoff.

Authors:  Zhenyu Wang; Pei Hua; Heng Dai; Rui Li; Beidou Xi; Dongwei Gui; Jin Zhang; Peter Krebs
Journal:  Environ Sci Ecotechnol       Date:  2020-02-08

2.  A comparative analysis of artificial neural networks and wavelet hybrid approaches to long-term toxic heavy metal prediction.

Authors:  Peifeng Li; Pei Hua; Dongwei Gui; Jie Niu; Peng Pei; Jin Zhang; Peter Krebs
Journal:  Sci Rep       Date:  2020-08-10       Impact factor: 4.379

  2 in total

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