Dioxin in the river Elbe

Chemosphere. 2017 Sep:183:229-241. doi: 10.1016/j.chemosphere.2017.05.090. Epub 2017 May 17.

Abstract

This paper provides a macro-analysis of the dioxin contamination in the river Elbe from the 1940s to the present. Based on different data sets, the historic dioxin concentration in the Elbe has been reconstructed. For the section between the tributary Mulde and Hamburg, during the 1940s, we find a concentration of about 1500 pg WHO-TEQ g-1. We argue that this dioxin contamination was caused mainly by emissions from a magnesium plant in Bitterfeld-Wolfen, whose effluents were discharged into a tributary of the river Mulde which flows into the Elbe. Dioxin pattern recognition with neural networks (Kohonen) confirms this. A model simulation shows that a hypothetical dioxin concentration of 10,000 pg WHO-TEQ g-1 in the tributary Mulde could have caused the reconstructed dioxin concentration of 1500 pg WHO-TEQ g-1 in the Elbe. The recent dioxin concentration (about 25-100 pg WHO-TEQ g-1) in the river Elbe, downstream the tributary Mulde, originates, according to our hypothesis, from emissions of the banks and the highly contaminated flood plains (transport of the particle bound dioxin). As other possible dioxin sources, the following could be excluded: the dioxin concentration in the Mulde, groynes, small ports, sport boat harbours, and extreme floods. Our hypothesis is supported by the results of pattern recognition techniques and a model simulation. According to these findings, we argue that remediation efforts to reduce the dioxin concentration in the river Elbe are unlikely to be successful.

Keywords: Century flood; Dioxin; Magnesium plant; Pattern recognition; River Elbe; Sediment.

Publication types

  • Historical Article

MeSH terms

  • Cluster Analysis
  • Dioxins / analysis*
  • Environmental Monitoring / history
  • Environmental Monitoring / methods*
  • Geologic Sediments / chemistry*
  • Germany
  • History, 20th Century
  • History, 21st Century
  • Models, Theoretical*
  • Neural Networks, Computer
  • Rivers / chemistry*
  • Water Pollutants, Chemical / analysis*

Substances

  • Dioxins
  • Water Pollutants, Chemical