Dioxin in the river Elbe

Accepted Manuscript Dioxin in the river Elbe Rainer Götz, Michael Bergemann, Burkhard Stachel, Gunther Umlauf PII:

S0045-6535(17)30794-4

DOI:

10.1016/j.chemosphere.2017.05.090

Reference:

CHEM 19305

To appear in:

ECSN

Received Date: 31 October 2016 Revised Date:

8 May 2017

Accepted Date: 15 May 2017

Please cite this article as: Götz, R., Bergemann, M., Stachel, B., Umlauf, G., Dioxin in the river Elbe, Chemosphere (2017), doi: 10.1016/j.chemosphere.2017.05.090. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Dioxin in the river Elbe

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Rainer Götz a, ∗, Michael Bergemann b, Burkhard Stachel c, Gunther Umlauf d

4 Nettelhof 6, D-22609 Hamburg, Germany

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b

State Ministry for the Environment and Energy of the Free and Hanseatic City of Hamburg,

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Department for Environmental Protection – Water Management, Neuenfelder Straße 19,

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D-21109 Hamburg, Germany

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Andersenstraße 32, D-22589 Hamburg, Germany

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European Commission, Joint Research Centre (JRC), Directorate D- Sustainable Resources,

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T.P. 121

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Via E. Fermi 2749, I-21027 Ispra (VA), Italy

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Keywords: dioxin, magnesium plant, river Elbe, sediment, pattern recognition, century flood

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Abstract

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This paper provides a macro-analysis of the dioxin contamination in the river Elbe from the

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1940s to the present. Based on different data sets, the historic dioxin concentration in the Elbe

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has been reconstructed. For the section between the tributary Mulde and Hamburg, during the

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1940s, we find a concentration of about 1500 pg WHO-TEQ g-1. We argue that this dioxin ∗

Corresponding author Phone: +49 40 821170 E-mail address: [email protected] (R. Götz) 1

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ACCEPTED MANUSCRIPT contamination was caused mainly by emissions from a magnesium plant in Bitterfeld-Wolfen,

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whose effluents were discharged into a tributary of the river Mulde which flows into the Elbe.

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Dioxin pattern recognition with neural networks (Kohonen) confirms this. A model

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simulation shows that a hypothetical dioxin concentration of 10,000 pg WHO-TEQ g-1 in the

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tributary Mulde could have caused the reconstructed dioxin concentration of 1500 pg WHO-

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TEQ g-1 in the Elbe. The recent dioxin concentration (about 25 - 100 pg WHO-TEQ g-1) in the

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river Elbe, downstream the tributary Mulde, originates, according to our hypothesis, from

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emissions of the banks and the highly contaminated flood plains (transport of the particle

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bound dioxin). As other possible dioxin sources, the following could be excluded: the dioxin

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concentration in the Mulde, groynes, small ports, sport boat harbours, and extreme floods.

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Our hypothesis is supported by the results of pattern recognition techniques and a model

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simulation. According to these findings, we argue that remediation efforts to reduce the

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dioxin concentration in the river Elbe are unlikely to be successful.

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1. Introduction

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The river Elbe (Fig.1a, Fig. 2a and Fig. 3a) is one of the major rivers in Central Europe. It

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originates in the Krkonoše Mountains of north-western Czech Republic before traversing

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Bohemia (Czech Republic), then Germany and flowing into the North Sea at Cuxhaven,

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110 km northwest of Hamburg (total length: 1,094 km, catchment area: 148,268 km2, 25

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million people) (FGG Elbe).

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For the most part, its dioxin concentration in the section between the mouth of the tributary

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Mulde and Hamburg is higher than the concentration in the river Rhine (Umweltbundesamt

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2007) and in the river Danube (Umlauf et al. 2011).

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Several publications have discussed the dioxin contamination of the river Elbe basin (Wilken

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et al. 1994, Götz et al. 1996, Götz et al. 1998, Götz and Lauer 2003, Umlauf et al. 2005,

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ACCEPTED MANUSCRIPT Stachel et al. 2006, Götz et al. 2007, Lechner 2007, Bunge et al. 2007, Umlauf et al. 2010,

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Umlauf et al. 2011, FGG Elbe 2011, LHW Sachsen-Anhalt 2007, LHW Sachsen-Anhalt

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2012, Tauw 2013, Baborowski and Heininger 2013, Förstner et al. 2016).

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In 1994, Wilken et al. reported that it could not be excluded that the high dioxin

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contamination in the floodplains of the Elbe results from dioxin transport throughout the river.

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The authors addressed chloralkali ectrolysis processes at the chemical production plant in

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Bitterfeld as a possible dioxin source. An evaluation with the cluster method neural networks

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(Kohonen) led to the hypothesis that the source of a considerable part of the dioxin pollution

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of the Elbe and its floodplains had been thermic processes in the metallurgical industry like

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magnesium and copper production at Bitterfeld. (Götz and Lauer 2003).

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In this study we reconstructed the historical dioxin contamination in the river Elbe, its

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tributaries and its floodplains at the Elbe section between the mouth of the Mulde and

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Hamburg (about 350 stream km) and gave a hypothesis of its cause. We believe this will help

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us to get a better understanding of the cause of the recent Elbe dioxin contamination. In the

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above mentioned literature, there are some suggestions to explain the recent dioxin

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concentrations in this Elbe section: elevated dioxin concentrations in the tributary Mulde,

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contaminated sediments in side structures of the river Elbe like groynes and small ports and

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extreme floods. In this study, we critically examine these proposals and investigate if they can

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be falsified. Our methodological approach is first to collect all the available significant

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measured dioxin data, then to arrange and classify them in tables and figures, and evaluate

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them by simple statistical methods. At a second stage of evaluation, we apply a simple mass

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balance model and extended cluster analysis with neural networks (Kohonen). Based on our

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results, we briefly address the question of whether it is possible to perform a remediation to

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reduce the dioxin concentration in the river Elbe.

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2. Methods 3

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2.1 Dioxins

78 For simplicity, the two groups of substances polychlorinated dibenzo-p-dioxins (PCDDs) and

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polychlorinated dibenzofurans (PCDFs) are referred as dioxins in this paper.

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The dioxin concentrations are reported as toxicity equivalents by the World Health

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Organization : WHO-TEQ (Van den Berg et al. 2006). In some few cases where we couldn’t

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transform the former I-TEQs (NATO/CCMS 1988) into WHO-TEQs the original I-TEQs are

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reported here.

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Dioxins in the rivers were measured in the solid phase (sediment, SPM (suspended particulate

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matter) and FDS (freshly deposited sediments, four-week composite samples)) because in the

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water phase the concentrations are too low, only a few fg/L were measured in the river Elbe

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(Götz et al. 1994).

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2.2.1 Data sources of the 388 dioxin samples used for cluster analyses with neural networks

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(Kohonen)

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To perform pattern recognition with neural networks (Kohonen) we could only take dioxin

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data sets which include the concentrations of the 17 dioxin toxic congeners together with the

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8 Cl4 to Cl7 dioxin homologues (see chapter 2.3).We took two kinds of sample groups: dioxin

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exposition samples taken in the Elbe catchment, and second external sample groups from

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potential dioxin sources. If there were similarities between the sources and the expositions in

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the Elbe catchment, we analysed if there could be a causal relationship. In comparison to a

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former cluster analyses (Götz and Lauer (2003) in this study we used for the sample group of 4

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ACCEPTED MANUSCRIPT the Elbe and its tributaries recent samples from the year 1998 to 2008. New is the sample

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group “dated sediment core samples from the Elbe” which may allow distinguishing between

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the historic and recent dioxin contamination of the Elbe. The sample groups “floodplains of

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the Spittelwasser”, “river Mulde (tributary of the Elbe)” were completed by more recent

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samples.

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In the dioxin source data set the sample groups “PCP (pentachlorphenol)” and “magnesium

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production (Norway)” were supplemented by 5 - respectively 16 samples, thus putting the

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cluster analyses on a broader foundation. The detailed justification that the magnesium

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samples of the Norwegian plant are representative for the dioxin emissions of the magnesium

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plant in Bitterfeld is described in Table SM.1 as Supplementary material. The other dioxin

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source samples were the sample groups “HCH production”, “sinter plants” and “chloralkali

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process”. We also collected dioxin patterns of the dioxin sources “PCB” and “pulp industry”,

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but these dioxin patterns were not stable, that means by test cluster analysis these patterns

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didn’t stay in one cluster, they were distributed over different clusters. Therefore these sample

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groups were not suitable for cluster analyses.

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The sources of the 388 samples are listed in Table 1 together with the sampling location, the

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matrix of the sample, the unit, the year of sampling, the number of samples in each group and

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the references in which the data were published, and the study design and the analytical

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methods are described. Additionally all measured dioxin concentrations of each of the 388

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samples - the 17 toxic congeners and the 8 Cl4 to Cl7 homologues - together with the

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calculated WHO-TEQs are given in Table SM.2 as Supplementary material.

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2.2.2 Data sources of the other dioxin samples

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In this paper we also evaluated dioxin concentrations of lots of other dioxin samples. But for

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these samples data of the 8 Cl4 to Cl7 dioxin homologues were not available. For this reason,

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these samples could not be added to the data set of the 388 samples for the cluster analyses. 5

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The sources of these samples are described in the references given when these dioxin samples

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were mentioned first.

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2.3 Cluster analyses with neural networks (Kohonen)

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We conducted cluster analyses with neural networks (Kohonen) with dioxin concentrations of

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388 dioxin samples in order to examine the similarity of dioxin patterns between different

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sample groups. First a transformation of the measured concentrations of the 17 highly toxic

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(2,3,7,8-substituted) dioxin and furan congeners for each sample of the 388 samples was

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performed (Hagenmaier et al. 1994). The concentrations of the individual congeners were

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divided by the corresponding Cl4 to Cl7 dioxin homologues. As 18th variable, the quotient of

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PCDD concentration and the total concentration of PCDD plus PCDF was added. A 388

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(rows) x 18 (columns) matrix was obtained. Mathematical, each row is a vector with 18

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components, which are the 18 transformed dioxin concentrations.

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Two levels of data reduction were performed. At the first level the 388 x 18 data matrix was

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clustered with a 7 x 7 Kohonen network (49 neurons). As output a 49 x 18 matrix (49

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codebook vectors, 18 weighting variables) was obtained. At the second level a clustering of

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the 49 codebook vectors was conducted with the method of the hierarchical cluster analysis

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(measure of similarity: cosine; clustering method: linkage between the groups) in order to

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generate cluster solutions. The applied SPSS computation program produced a table in which

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the 388 dioxin samples together with their cluster membership were listed.

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In summary, the dioxin patterns that are the 18 transformed dioxin concentrations of each of

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the 388 samples were aggregated into clusters in such a way that the patterns in any cluster

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are as similar to each other as possible within one cluster and as different as possible from the

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patterns in the other clusters. A more detailed description of the two stage procedure can be

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found in Samarasinghe (2007).

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The computations for the Kohonen network were carried out using SPSS Neural Connection

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2.1 for Windows, Chicago in combination with SPSS 10.07 for Windows, Chicago. The

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hierarchical cluster analyses were performed using SPSS 13 for Windows, Chicago.

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To simulate the dependency of the dioxin concentration in the Elbe on the dioxin content in

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its tributaries Mulde and Saale, we have created a simplified model: The dioxin contaminated

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SPM of Mulde and Saale flow into the Elbe, where they mix with the much less dioxin

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contaminated SPM of the Elbe, upstream of the Mulde. The mix of these three types of SPM

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make up the theoretic dioxin concentration in the Elbe (CElbe, theoretical) downstream of the

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Mulde and Saale. You can compare this calculated dioxin concentration with the measured

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dioxin mean value of 52 WHO-TEQ g-1 in the Elbe at Magdeburg.

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That is to say, CElbe, theoretical can be expressed as a linear function of the dioxin concentration

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of the river Mulde CMulde.:

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U=

L1 ( L1 + L 2 + L 3

(3)

V=

(C 2 * L 2 + C 3* L 3) ( L1 + L 2 + L 3)

(4)

L1 =

(2)

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CElbe,theoretical = U * CMulde + V

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A1* B1 1000

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(5)

L2 =

A2 * B2 1000

(6)

L3 =

A3* B3 1000

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A1 = SPM concentration in the Mulde; A2= SPM concentration in the Saale; A3= SPM

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concentration in the Elbe, upstream of the Mulde;

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B1= discharge in the Mulde; B2 = discharge in the Saale; B3 = discharge in the Elbe,

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upstream of the Mulde;

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L1= SPM load in the Mulde; L2 = SPM load in the Saale; L3= SPM load in the Elbe,

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upstream of the Mulde;

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CMulde = dioxin concentration in SPM in the Mulde; C2 = dioxin concentration in SPM in the

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Saale; C3 = dioxin concentration in SPM in the Elbe, upstream of the Mulde.

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The SPM concentration was measured in mg/L, the discharge in m3/s and the dioxin

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concentration in SPM in pg WHO-TEQ g-1.

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The data for the SPM concentration, the discharge and the dioxin concentration for the Mulde

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were taken at the sampling site Dessau, for the Saale at Groß Rosenburg and for the Elbe,

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upstream of the Mulde, at Wittenberg.

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Employing equation (1), we have calculated the dioxin concentration in the Elbe, downstream

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of the Mulde and the Saale (CElbe, theoretical ) for different scenarios.

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3. Results and discussion

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3.1 Dioxin contamination of the river Elbe, downstream the tributary Mulde, in the 1940s

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1945 to 2008. The dioxin content in the Elbe from 1945 to 1990 was reconstructed on the

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basis of the investigation of two sediment cores from the Elbe, which were dated with a

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radiochemical method, and soil samples from the Bille residential estate in Hamburg-

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Moorfleet. One sediment core was obtained from Heuckenlock, a flood plain of the river Elbe

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southeast of Hamburg (river Elbe, km 610.5); the other was obtained upstream of Hamburg

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from nearby Pevestorf (river Elbe, km 485). The Heuckenlock sediment core layer, dated to

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1947, shows a high dioxin concentration of 2050 pg WHO-TEQ g-1. In the Pevestorf sediment

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core, extremely high dioxin concentrations of 3310 and 6880 pg WHO-TEQ g-1 were found in

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two layers dated to 1952 and 1959. Later there was an abrupt decline of the dioxin

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concentration (Hamburger Umweltberichte 1999; Götz et al. 2007).

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The Bille residential estate was built on an area where dredged sediments from the Port of

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Hamburg, through which the Elbe flows, were deposited in the 1940s. Dioxin analyses were

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conducted in 25 soil samples (9 samples: 1080 - 3860 pg WHO-TEQ g-1; 16 samples: 110 -

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740 pg WHO-TEQ g-1) (Umweltbehörde 1991, Götz and Lauer 2003). There are no reports of

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any significant dioxin sources in the Port of Hamburg. Thus it can be concluded

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that the high dioxin contents in top soils of the Bille residential estate stem from the high

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dioxin contaminated SPM and sediments from the Elbe (Fig. 1b) that were transported into

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the Port and deposited there.

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Additional evidence for our hypothesis of the high dioxin contamination in the Elbe in the

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1940s is provided by the highly dioxin contaminated floodplains of the Elbe with maximum

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values, which ranges from 1890 to 2510 pg WHO-TEQ g-1 (Fig. 2b (Umlauf et al. 2004,

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Umlauf et al. 2005) and Fig. 2c (Niedersächsischer Untersuchungsbericht 1993,

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Niedersächsischer Untersuchungsbericht 2004, Götz and Lauer 2003)). Because the

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floodplains were contaminated through floods of the Elbe, the historic dioxin concentration in

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ACCEPTED MANUSCRIPT the Elbe (SPM, sediment) must have been at least as high as the resulting concentration in the

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floodplains (soil).

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Based on this reasoning, we argue furthermore, that dioxin concentrations in the Elbe

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upstream of the tributary Mulde in the 1940s must have been as low as today's concentration

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in the Elbe floodplains upstream of Mulde (ranging between 7 – 40 pg WHO-TEQ g-1) (Fig.

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2b). The reason is simple. If the old dioxin concentration in the Elbe (upstream Mulde) had

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been high, the concentration in the floodplains would also have been high and would still be

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detectable there today. But this is not the case.

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The question is what was the cause for the extremely high dioxin concentration in the river

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Elbe and its floodplains, downstream the Mulde?

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At the Mulde, the industry complex Bitterfeld-Wolfen is located, which already existed in the

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1940s. Its history is well documented (Bitterfelder Chronik 1993, Fischer 2003, Hackenholz

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2004, Harbodt 2006). In the past there must have been large dioxin emissions there, as

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indicated by soil samples at the plant ground of the chemical combinate Bitterfeld of up to

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250,000 pg I-TEQ g-1 (Wilken et al. 1994). Moreover, in the past, highly contaminated

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sewage waters from these industrial plants were discharged into the creek Spittelwasser,

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which flows into the river Mulde (Wilken et al. 1994, Fischer 2003).

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Supporting evidence comes from very high dioxin concentrations in the creek Spittelwasser

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and its floodplains (Wilken et al. 1994, Götz and Lauer 2003, Schwartz et al. 2006, LHW

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Sachsen-Anhalt, unpublished results). The maximum values are: 41,600 pg WHO-TEQ g-1

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(undated sediment core), 157,000 pg WHO-TEQ g-1 (floodplain) and 203,000 pg I-TEQ g-1

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(floodplain, undated soil core). All values are listed in Table SM.3 as Supplementary material.

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Because the dioxin concentrations are so high and some of these high dioxin concentrations

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were found in deeper layers, we believe these old dioxin contents might originate from the

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1940s.

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floodplain were not available. But because of the high historical dioxin contents found for the

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Spittelwasser, one might suppose the historical dioxin contamination in the Mulde have been

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high as well.

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Our hypothesis is that the main source of the historical dioxin contamination of the

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hydrological system Spittelwasser-Mulde-Elbe and its floodplains were dioxin emissions

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from a magnesium plant in Bitterfeld in the 1940s. The plant produced large amounts of

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magnesium from the 1930s to 1945 with 3,900 tons in 1944 (Fischer 2003).

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Support for this hypothesis is found in the fact that after the magnesium plant had stopped its

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production in 1945 (Fischer 2003), the dioxin concentration in the Elbe abruptly decreased

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(Fig. 1b).

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We have conducted extended cluster analyses with neural networks (Kohonen) to further

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substantiate this hypothesis. Table 2 summarizes the classification results for the six and

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seven cluster solution with reference to the respective dioxin sample groups from Table 1. In

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comparison to Götz and Lauer (2003) we got a more differentiated picture.

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From the algorithms of the cluster analysis (chapter 2.3) it follows that the similarity between

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the dioxin patterns in the Bitterfeld-Elbe A and in the Bitterfeld-Elbe B clusters (7 cluster

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solution) is greater than between the dioxin patterns in the Bitterfeld-Elbe cluster (6 cluster

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solution).

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The old Elbe catchment dioxin samples including a part of the Elbe floodplains are grouped

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together with the samples of the magnesium production in the Bitterfeld-Elbe-A cluster (7

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cluster solution) (Table 2). That means that there is a great pattern similarity between the old

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Elbe catchment contamination and the dioxin source magnesium production. This finding

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indicates that there is a causal relationship between the magnesium production in Bitterfeld

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and the historical Elbe catchment dioxin pollution from the 1940s.

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ACCEPTED MANUSCRIPT The pattern similarity between the dioxin source magnesium and the recent contamination of

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the Elbe catchment is less, which follows from the grouping of these samples (together with

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the old Elbe catchment contamination) only at the 6 cluster solution level in the Bitterfeld-

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Elbe cluster. But the recent Elbe catchment pollution show a great pattern similarity with the

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floodplain samples since they are grouped in the Bitterfeld-Elbe B cluster (7 cluster level).

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These finding is in agreement with our hypothesis mentioned in chapter 3.3 that the recent

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Elbe pollution stems from flood plain emissions (transport of particle bound dioxin). We

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suppose that the dioxin patterns from the floodplains date back to the old magnesium

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production, but over time the patterns of the top soil layers in the floodplains, from which the

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emissions start, may have been changed due to mixing with other unknown dioxin sources.

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Therefore, this part of the floodplain dioxin patterns may exhibit a lower degree of similarity

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to the patterns of the magnesium samples.

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The source sample groups “PCP” and “HCH production” are in separate clusters indicating

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that these organochlorine industry sources were only of minor importance for the dioxin

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contamination of the Elbe catchment.

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There was no significant copper production and there were no important sinter plants in

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Bitterfeld-Wolfen (Bitterfelder Chronik 1993). Thus there is no reason to discuss their cluster

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membership in this paper.

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It should also be noted that the Bitterfeld magnesium company had two subsidiaries, one in

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Stassfurt at the creek Bode which flows into the Saale, a tributary of the Elbe, the other in

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Aaken on the Elbe (stream km 275). The magnesium production in both factories stopped in

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1945 (Fischer 2003). Unfortunately, there are no dioxin data at all to answer the question of

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whether, or to what extent, they contributed to the contamination of the Elbe.

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The question arises how high the dioxin concentration in the tributary Mulde must have been

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in the 1940s to get a concentration of about 1500 pg WHO-TEQ g-1 in the Elbe which could

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have been the concentration in the 1940s. Our model simulations show that a dioxin

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concentration of 10,000 pg WHO-TEQ g-1 in the river Mulde must indeed have been

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necessary to reach a concentration of about 1500 pg WHO-TEQ g-1 in the Elbe (Table3,

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scenario 1). As mentioned above, this high dioxin concentration for the Mulde is a realistic

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assumption for the 1940s.

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3.2 Dioxin contamination of the river Elbe between 1960 and 1990

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The reconstructed dioxin concentrations in the river Elbe between the 1960s and the 1980s

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(Fig. 1b) show values in the range of 180 and 580 pg WHO-TEQ g-1. The dioxin sources for

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this contamination are unknown. Up until 1993 high contaminated sewage waters were

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discharged into the creek Spittelwasser (Fischer 2003). This gives rise to the suspicion that

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this could be the cause of the above mentioned contamination in the Elbe.

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3.3 Dioxin contamination of the river Elbe and its tributaries since 1990

3.3.1 Dioxin longitudinal profiles of the river Elbe

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Since the early 1990s six dioxin examination series of solid matter in the river Elbe have been

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conducted (FDS, sediments), with sampling sites from the German-Czech border (and 2008

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even in the Czech Republic itself) to the North Sea (1994, 1995, 1998, 1998, 2002, 2008)

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(Hamburger Umweltberichte 1999, Umweltbundesamt 2002, Götz and Lauer 2003, Knoth et

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al. 2003, Umlauf et al. 2010, Umlauf et al. 2011) (Fig. 3b and c). The Elbe downstream

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profiles of the various years are similar. One important feature is the marked and abrupt

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increase in dioxin concentrations (dioxin jump) briefly after the confluence of the river

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Mulde. Fig. 3d shows this dioxin jump between Wittenberg (km 214.1, upstream the Mulde)

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(Stachel et al. 2004, LHW Sachsen-Anhalt, unpublished results, BfG, unpublished results)

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Anhalt, unpublished results).

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The dioxin concentration in the river Elbe below the tributary Mulde exceeds the upper limit

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of 20 pg WHO-TEQ g-1 dw (FGG Elbe 2015) in SPM and sediment.

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Eels (fatty fish) taken from the river Elbe during the years 1996 to 2002 exceed in most cases

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the maximum level of 3.5 pg WHO-TEQ g-1 wet weight for muscle meat of wild caught eel

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(Angilla anguilla) of the European Commission (Stachel et al. 2007, European Commission

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2011).

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3.3.2 Hypothesis of the cause of the recent dioxin concentration in the Elbe

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The question is: what is the source of the recent dioxin concentration in the Elbe downstream

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Mulde to Hamburg (350 km), which ranges from about 25 to 100 pg WHO-TEQ g-1 (Fig. 3 b

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and c). Our hypothesis is that the main sources are dioxin emissions from the dioxin

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contaminated Elbe floodplains. This hypothesis is supported by several observations.

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Upstream of the Mulde the dioxin concentrations of the Elbe are much lower and lie in the

345

range of 5 to 20 pg WHO-TEQ g-1 (Fig. 3b and c). According to the results of the cluster

346

analyses with neural networks (Kohonen) the dioxin patterns of these sample group, which

347

can not be contaminated by the Bitterfeld region, fall in the “atmosphere cluster” (Table 2),

348

indicating atmospheric deposition as a dominant source for this Elbe region. Thus, we have to

349

exclude that the source is upstream of the Mulde.

350

The sample group “inner city surface waters (not connected with the river Elbe), Hamburg”,

351

which was taken to control the classification method, is also grouped in the “atmosphere

352

cluster” (Table 2).

353

The next question is, whether the recent dioxin concentration in the Mulde (about 100 pg

354

WHO-TEQ g-1) is the cause of the recent dioxin contents in the Elbe downstream the Mulde,

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ACCEPTED MANUSCRIPT similar to the situation in the 1940s. The dioxin concentration of the river Mulde (at Dessau)

356

from 1994 to 2014 is plotted in Fig. SM.1 as Supplementary material (Stachel et al. 2004,

357

Umlauf et al. 2011, LHW Sachsen-Anhalt, unpublished results). The dioxin concentration

358

declines from about 350 pg WHO-TEQ g-1 in 1994/1995 to about 100 pg WHO-TEQ g-1 in

359

2000, but has remained constant since then. For 74 samples (2001-2014) the mean is 94 ± 7.1

360

pg WHO-TEQ g-1. We can exclude the Mulde as a source because our model simulation

361

shows that the recent dioxin concentration in the Mulde is too low to increase significantly the

362

dioxin concentration in the Elbe from 9.5 pg WHO-TEQ g-1 at Wittenberg, upstream the

363

tributary Mulde, to 52.2 pg WHO-TEQ g-1 at Magdeburg, downstream the Mulde (Fig. 3d)

364

(Table 3, scenario 2 and 3).

365

In our model calculation we have not taken into consideration atmospheric deposition as a

366

potential dioxin source. We believe it is not a significant cause of the dioxin jump in the Elbe,

367

and we therefore have not included it in our model. A detailed explanation is given in Table

368

SM.4 as Supplementary material.

369

The recent dioxin concentrations in sediment of groynes, small ports, sport boat harbours

370

along the Elbe, are compiled in Table SM.5 as Supplementary material (Hamburger

371

Umweltberichte 1994, Hamburger Umweltberichte 1999, Hamburger Umweltberichte 2000,

372

Umweltbundesamt 2002, Knoth et al. 2003, Umlauf et al. 2010, Umlauf et al. 2011). The

373

concentrations are in the same magnitude as those of the Elbe and therefore can also be

374

excluded as a secondary dioxin source for the Elbe.

375

One could also surmise that the so-called “century flood” in August 2002 led to elevated

376

dioxin concentrations in the Elbe. Dioxin measurements exist which cover the days of the

377

flood maximum (Stachel et al. 2004). The compiled data and the results of their evaluation are

378

listed in Table SM.6 as Supplementary material (Umlauf et al. 2011, LHW Sachsen-Anhalt,

379

unpublished results). The data show that the dioxin concentrations in the Mulde and in the

380

Elbe downstream the Mulde (at Magdeburg) were not significantly heightened during the

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ACCEPTED MANUSCRIPT century flood. Furthermore, no correlation between the water discharge and the dioxin

382

concentration was found. Additionally our model simulation (Table 3, scenario 4) shows that

383

with the hydrological parameters during the century flood the Mulde could not be the cause of

384

a significant increase of the dioxin concentration in the Elbe.

385

After excluding all these possible dioxin sources, our argument is that only emissions from

386

the flood plains (transport of particle-bound dioxin) as the main source for the recent dioxin

387

contamination in the Elbe remain. The results of the cluster analyses with neural networks

388

(Kohonen), which show that there is a similarity between the dioxin pattern of the flood plains

389

and the dioxin patterns of the recent dioxin samples (1998 to 2008) of the Elbe (Table 2, 7

390

cluster solution), provide support for this hypothesis (see the section about the cluster

391

analyses in chapter 3.1).

392

Fig. SM.2 in Supplementary material schematically illustrates the supposed dioxin flows and

393

concentrations in the 1940s and the recent dioxin flows and concentrations.

394

It should be stated that in comparison to Götz and Lauer (2003) the reconstruction of the

395

historic dioxin concentration of the river Elbe, the suggested cause of the recent dioxin

396

contamination and the conclusion about remediation possibilities are new findings. Different

397

model simulations were applied. The cause of the historic dioxin contamination could be

398

described with better evidence.

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4. Conclusions

402

Our analysis has shown that in the 1940s the river Elbe and its floodplains were probably

403

partly contaminated with dioxin over a distance of about 350 km (from the Mulde mouth till

404

Hamburg) resulting in 1500 pg WHO-TEQ g-1 mainly due to a magnesium plant in Bitterfeld-

405

Wolfen near the tributary Mulde. Production at this plant was stopped in 1945. Nowadays the

406

dioxin concentration in the river Elbe is much lower (about 25 to 100 pg WHO-TEQ g-1) (Fig. 16

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ACCEPTED MANUSCRIPT 3b and c). Our analysis indicates that this relative low dioxin contamination in the river Elbe

408

is caused by dioxin emissions from the floodplains (transport of particle-bound dioxin).

409

Given the evidence discussed above, we suppose that it seems practically impossible to

410

perform a remediation of the Elbe to reduce the dioxin concentration in the Elbe, because it

411

would be necessary to remediate the high contaminated areas in the floodplains and maybe in

412

the banks over a distance of about 350 km.

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413 Acknowledgement

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We gratefully acknowledge the delivery of dioxin data from the Landesamt für

417

Hochwasserschutz und Wasserwirtschaft Sachsen-Anhalt, Magdeburg, Germany and from

418

Bundesanstalt für Gewässerkunde, Koblenz, Germany.

419

We would also like to thank Elias Götz, Georg Götz and Mark Weeks for language

420

suggestions and corrections and Ute Ehrhorn for drafting the maps of the Elbe.

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Fig. 1. Dioxin concentration in the river Elbe from 1945 to 2008. a: Map of the river Elbe. b: Reconstructed dioxin concentration 1945 to 1990 and measured dioxin concentration 1990 to 2008.

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c: Measured dioxin concentration 1990 to 2008 at Hamburg-Bunthaus with 95 % confidence bands for the linear regression. The linear regression is significant with 95 % (F-Test). The slope is significant (95 %) negative. The correlation with R=0.64 is weak.

The samples were taken from SPM (suspended particulate matter, continuous centrifuge), FDS (freshly

Fig. 2. Dioxin concentrations in floodplains of the river Elbe.

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deposited sediments, four-week composite samples from monitoring stations) and surface sediments.

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a: Map of the river Elbe with sampling points of the floodplains.

b: Dioxin concentrations (soil samples) in floodplains of the river Elbe. The samples were taken in 2003. c: Dioxin concentrations (soil samples) in floodplains of the river Elbe. The samples were taken in 1993 and 2002.

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Fig. 3. Dioxin longitudinal profiles of the river Elbe. a: Map of the river Elbe with sampling points.

b: Dioxin concentrations of the longitudinal profiles from 1994, 1995 and 1998. The samples were taken from FDS (freshly deposited sediments, four-week composite samples from monitoring stations).

EP

c: Dioxin concentrations of the longitudinal profiles from 2002 and 2008. For the Elbe longitudinal profile 2002 surface sediment samples and for the Elbe profile 2008 surface sediment samples and FDS samples were taken.

AC C

d: dioxin jump in the river Elbe at Wittenberg/Magdeburg; mean at Wittenburg: 9.5 pg WHO-TEQ g-1, mean at Magdeburg: 52.2 pg WHO-TEQ g-1, difference of the means: 42.7 pg WHO-TEQ g-1 (95 % lower limit: 35.4 pg WHO-TEQ g-1, 95 % upper limit: 61.9 pg WHO-TEQ g-1). The samples were taken from FDS and SPM (suspended particulate matter, continuous centrifuge).

ACCEPTED MANUSCRIPT Table 1. List of samples with dioxin patterns used for cluster analyses with neural networks (Kohonen) 388 samples matrix

unit

river Elbe Elbe (upstream the tributary Mulde) from Paradubice-Semtin (stream km -237) to Dommitzsch sediment, FDS pg g-1 dw (stream km 173) Elbe (downstream tributary Mulde to Cuxhaven,North Sea) from Magdeburg (stream km 318.1) to Cuxhaven (stream sediment, FDS, pg g-1 dw km 725.2) SPM

year of sampling

number of samples

References

2008

11

Umlauf et al. 2011

1998-2008

70

Hamburger Umweltberichte 1999; Umlauf et al. 2011

RI PT

sample groups

sediment

pg g-1 dw

1998-2008

7

Umlauf et al. 2011

dated sediment core samples from the river Elbe (Hamburg Heuckenlock (stream km 610.5) and Pevestorf (stream km 485), Germany)

sediment core

pg g-1 dw

1995

18

Hamburger Umweltberichte 1999; Götz et al. 2007

soil

pg g-1 dw

floodplains of the river Elbe flood plains of the river Elbe in Lower Saxony, Germany (from Assel, stream km 666 to Gorleben, stream km 491)

region Bitterfeld (Germany)

creek Spittelwasser (tributary of the river Mulde) flood plains of the Spittelwasser

21

Niedersächsischer Untersuchungsbericht 1993; Götz and Lauer 2003

pg g-1 dw pg g-1 dw pg g-1 dw pg g-1 dw pg g-1 dw

2008 1998, 2008 1998 2008 2008

1 3 2 1 1

Hamburger Umweltberichte 1999; Umlauf et al. 2011

sediment, sediment core, pg g-1 dw SPM

1992, 1994,1995, 2008

25

Götz and Lauer 2003; Umlauf et al. 2011

pg g-1 dw

1991, 1994, 2004 1992, 1995, 1998, 1999,2000,2 008

FDS FDS FDS sediment FDS

sediment, SPM, FDS

pg g-1 dw

22

Götz and Lauer 2003

49

Götz and Lauer 2003

ng g-1

9

Hagenmaier et al. 1987; Masunaga et al. 2001; Seike et al. 2003

pg g-1 dw

5

Götz and Lauer 2003; Weber and Varbelow 2012

atmospheric samples (dust precipitation, Hamburg)

pg m-2 d-1

atmospheric samples (airborne particles, Hamburg)

fg m-3

1990, 1991, 1993, 1995 1993, 1994, 1995

AC C

17

Götz and Lauer 2003; Schwartz et al. 2006 Hamburger Umweltberichte1999; Umlauf et al. 2011 Götz and Lauer 2003; Hamburger Umweltberichte 2000

1992, 1997, 1998, 2000

sediment

5

18

pg g-1 dw

inner city surface waters (not connected to the river Elbe), Hamburg (Germany)

Umweltbehörde 1991; Götz and Lauer 2003

1993

soil, soil core

EP

river Mulde (tributary of the Elbe)

25

pg g-1 dw

soil

TE D

Tributaries of the Elbe (without the tributary Mulde) Bode (joins the river Saale) Saale (joins the Elbe at about stream km 290) Schwarze Elster (joins the Elbe at about stream km 199) Stoer (joins the Elbe at about stream km 679) Moldau (joins the river Elbe at about stream km -110)

1991, 1992

M AN U

Bille residential estate, Hamburg (Germany) (The areas of the Bille residential estate were designated as disposal sites for the dredging material from the Elbe and the Port of Hamburg in the 1940s)

SC

Hamburg Port (Elbe)

atmosphere, Hamburg (Germany)

Environmental samples classifified by dioxin source (external samples for dioxin pattern comparision) PCP (pentachlorophenol) commercial PCP and PCP-Na products, PCP based agrichemical formulations

solid phase

HCH production in Hamburg (Germany) The HCH production samples stem from dioxin emissions of a former pesticide plant (lindane, 2,4,5-T) in HamburgMoorfleet. The sediment core samples arise from a canal sediment core (Port of Hamburg) in front of the pesticide plant, in which effluents of the plant were discharged.

ACCEPTED MANUSCRIPT The oil leachate samples are from fluid chemical waste the oil former pesticide plant had dumped on the sanitary landfill Hamburg-Georgswerder. magnesium production (Norway) sediment samples near a magnesium factory, Grenlandsfjords, Norway

sediment

ng g-1

15

Götz and Lauer 2003, Götz et al. 2013

pg g-1 dw

22

Oehme et al. 1989; Ishak et al. 2009

pg g-1 dw

24

Fresenius 1991; Theisen et al. 1993

sinter plants in North Rhine-Westphalia (Germany) The samples are clean gas samples from emmissions of two ore sinter plants. In the ore sinterplants iron ore was prepared for the blast furnaces, in which pig iron was produced.

ng m-3

gas

pg g-1 dw

AC C

EP

TE D

M AN U

chloralkali process (Sweden) The samples are sludge samples from graphite electrodes used in the chloralkali process in a chloralkali plant in sludge Sweden.

15

SC

"Kieselrot", siliceous slag residues, were produced in large quantities during the chlorinating roasting of copper ore in Marsberg. "Kieselrot" was used in the 1950s and 19560s solid phase as a covering material for sportgrounds and playgrounds.The soil samples listed here were taken from sportgrounds and playgrounds in Frankfurt, Germany.

RI PT

copper production (Germany)

2

Götz and Lauer 2003

Rappe et al. 1991

ACCEPTED MANUSCRIPT

RI PT

Table 2. Classification results: 388 dioxin samples, neural networks (Kohonen), 49 neurons. n: number of samples. (The 7 single samples from the Elbe tributaries Schwarze Elster, Bode, Saale and Stör are not listed here, because cluster results of single samples of a sample group can not be taken as truly representative. 11 samples from different sample groups were missclassified and not listed in the Table.) 7 clusters (sample groups)

Bitterfeld-Elbe cluster region Bitterfeld-Wolfen river Mulde (n=17)

Bitterfeld-Elbe-A cluster region Bitterfeld-Wolfen river Mulde (n=1)

SC

6 clusters (sample groups)

atmosphere cluster atmosphere (airborne particles) (n=48) atmosphere (dust precipation) (n=21) river Elbe (upstream river Mulde) (n=12) inner city surface waters (Hamburg) (n=14) PCP cluster (n=8) HCH cluster (n=20)

creek Spittelwasser and floodplains of the Spittelwasser (n=10) dated sediment core samples of the river Elbe (n=4) flood plains of river Elbe (Lower Saxony) (n=9) Bille residential estate (Hamburg Moorfleet) (n=23) magnesium production (n=22) Bitterfeld-Elbe-B cluster region Bitterfeld-Wolfen river Mulde (n=16) creek Spittelwasser and floodplains of the Spittelwasser (n=20) river Elbe (downstream river Mulde to Port of Hamburg) (n=73) (1998-2008) dated sediment core samples of river Elbe (n=14) flood plains of river Elbe (Lower Saxony) (n=12) Bille residential estate (Hamburg Moorfleet) (n=2) copper production (n=24) atmosphere cluster atmosphere (airborne particles) (n=48) atmosphere (dust precipation) (n=21) river Elbe (upstream river Mulde) (n=12) inner city surface waters (Hamburg) (n=14) PCP cluster (n=8) HCH cluster (n=20)

sinter plants cluster (n=15) (chloralkali process cluster (n=2))

sinter plants cluster (n=15) (chloralkali process cluster (n=2))

AC C

EP

TE D

M AN U

creek Spittelwasser and floodplains of the Spittelwasser (n=30) river Elbe (downstream river Mulde to Port of Hamburg) (n=73) (1998-2008) dated sediment core samples of river Elbe (n=18) flood plains of river Elbe (Lower Saxony) (n=21) Bille residential estate (Hamburg Moorfleet) (n=25) magnesium production (n=22) copper production (n=24)

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

The samples of the old Elbe catchment contamination in the Bitterfeld-Elbe-A cluster are: the dated sediment core layers from the 1940s and 1950s of the Elbe (Pevesdorf : 6880 and 3310 pg WHO-TEQ g-1; Hamburg-Heuckenlock: 2050 pg WHO-TEQ g-1), all soil samples of the Bille residential estate in HamburgMoorfleet which stem from dredged sediments from the Elbe and the Port of Hamburg from the 1940s (up to 3360 pg WHO-TEQ g-1), and a part of the soil samples from the flood plains of the Elbe in Lower Saxony, which most likely are old contaminations from the 1940s too (up to 2170 pg WHO-TEQ g-1), the dioxin patterns of the high dioxin contaminated samples from the Spittelwasser and its floodplain (the undated sediment core layers (up to 14,540 pg WHOTEQ g-1), the floodplain samples (35,860 and 157,000 pg WHO-TEQ g-1) and the soil core sample (11,790 pg WHO-TEQ g-1)). The chloralkali process cluster is not representative because there are only two samples in it.

ACCEPTED MANUSCRIPT

Table 3. Results of the model simulations with equation (1)

SPM concentration

Scenario 2 (mean for A1, A2, A3, B1, B2, and B3 in 2008) SPM concentration

mg/ L

mg/ L

Scenario 3 (maximum values for A1, A2, A3, B1, B2 and B3 in 2008) SPM concentration

A1

25

A1

6

A1

Saale (Groß Rosenburg)

A2

22

A2

22

A2

Elbe (Wittenberg)

A3

17

A3

17

A3

discharge

m3/s

discharge

m3/s

55

B1

55

Saale (Groß Rosenburg)

B2

108

B2

108

Elbe (Wittenberg)

B3

304

B3

304

dioxin concentration in SPM

pg WHOTEQ g-1

dioxin concentration in SPM

35

C2

Elbe (Wittenberg)

9.5

C3

results of the model calculation with equation (1)

10000

C (Elbe,theoretical), downstream Mulde

1560

dioxin in SPM

EP

pg WHOTEQ g-1

C (Mulde)

pg WHOTEQ g-1

C (Mulde)

mg/ L

Scenario 4 (century flood august 2002)

SPM concentration

mg/ L

7.9

A1

27

A2

20

39

A3

160

m3/s

discharge

140

m3/s

B1

151

B1

678

B2

228

B2

358

B3

794

B3

3990

dioxin concentration in SPM

pg WHOTEQ g-1

dioxin concentration in SPM

pg WHOTEQ g-1

35

C2

35

35

9.5

C3

9.5

9.5

results of the model calculation with equation (1)

AC C

dioxin in SPM

TE D

Saale (Groß Rosenburg)

discharge

M AN U

B1

SC

Mulde (Dessau)

Mulde (Dessau)

RI PT

Scenario 1 (hypothetical situation in the 1940s)

results of the model calculation with equation (1)

pg WHOTEQ g-1

0

dioxin in SPM

C (Mulde)

results of the model calculation with equation (1)

pg WHOTEQ g-1

0

C (Elbe,theoretical), downstream Mulde

16.8

C (Elbe,theoretical), downstream Mulde

13.3

C (Mulde)

100

C (Mulde)

100

C (Elbe,theoretical), downstream Mulde

21

C (Elbe,theoretical), downstream Mulde

16.4

dioxin in SPM

C (Mulde) mean dioxin value measured during the flood C (Elbe,theoretical), downstream Mulde

C (Mulde) minimum dioxin value measured during the flood C (Elbe,theoretical), downstream Mulde

pg WHOTEQ g-1

90

20

51

15.1

ACCEPTED MANUSCRIPT

1000

C (Elbe,theoretical), downstream Mulde

58.7

C (Mulde) maximum dioxin value measured during the flood C (Elbe,theoretical), downstream Mulde

AC C

EP

TE D

M AN U

SC

RI PT

C (Mulde)

156

28.5

figure_1 revised.doc

ACCEPTED MANUSCRIPT

M AN U

SC

RI PT

a

b Elbe 3500

6880 Pevestorf

sediment core Pevestorf km 485

2500

FDS/SPM/sediment Hamburg-Bunthaus km 609.8

2000

sediment Port of Hamburg, Elbe (Bille residential estate)

TE D

WHO-TEQ (pg g-1 dw)

3000

1500 1000

0 45 19

55 19

60 19

AC C

50 19

EP

500

WHO-TEQ (pg g-1 dw)

c

sedimentcore Hamburg-Heuckenlock km 610.5

160 140

65 19

70 19

75 19

80 19

85 19

90 19

95 19

00 20

Elbe, Hamburg-Bunthaus km 609.8 (SPM, FDS, sediment)

120 100 80 60 40 20 0 1990

1995

2000

2005

2008

05 20

10 20

km 6 66

1400 1200 1000 800 600 400 200 0

AC C EP

c 1600

Ham burg

Rönn e km 58 5; Sas s km 5 e ndo 81 r f km Sas s 568 e ndo r f km Sas s 568 e ndo r f km Sas s 568 e ndo r f km 568 G arl s Ne u to rf k G ar g m 559 e km 544;k Ties s m 53 au km 9 G orl e 52 8; ben 4 km 5 92;V 13 Sc hn i etze ac ke 4 87. nb ur 5 g km 47 4. 5

As se l

WHO-TEQ (pg g-1 dw)

Hamburg

2350

Magdeburg (km 318.1) dow nstream Mulde

dioxin in floodplains of the Elbe (soil samples)

2510

km 1 28 pa km 114

berg

Zsch e

Mühl

41

dioxin in floodplains of the Elbe (soil samples)

SC

1890

km 2

RI PT

a

Wö rl it z

1600 1400 1200 1000 800 600 400 200 0

M AN U

b

TE D

Sass endo rf km 56 8 Neu G arg e km 544 Po m mau km 5 32 Gorle b en km 4 Schn 92 a cke nb ur g 47 4.5 Lüt ke nw is ch km 47 3 Schö nb er g km 438 Tan g ermü nde k m 38 7 Gli nd e km 301 Stec kb y k m 28 5

WHO-TEQ (pg g-1 dw)

figure_2_revised.doc

ACCEPTED MANUSCRIPT

Saale km 290.5 Mulde km 259.5

Wittenberg (km 214.1) upstream Mulde

WHO-TEQ (pg g-1 dw)

AC C

0

c 120

100 2002

80 2008

d 200

1994

1998 Ham burg

60

40

20

2002

TE D

150

2006 Magdeburg

0

Magdeburg km 318.1

50

2010

2014

Wittenberg

april 1994

km 290.5

Saale

august 1998

140

2002

2006

RI PT

river Elbe 1994, 1995 and 1998 (FDS)

Schmilka, km 4.1

april 1998

Dommitzsch, km 172.6

august 1995 Mulde

SC

20

Magdeburg, km 318.1

Ham burg

river Elbe 2002 and 2008 (FDS, sediment)

M AN U

Cumlosen, km 470

40

Schnackenburg, km 474.5

60

Bunthaus, km 609.8

b 120

Seemannshöft, km 628.8

80

Blankenese, km 634.3

100

Grauerort, km 660.5

Cuxhaven, km 725.2

WHO-TEQ (pg g-1 dw)

a

W Dom i ttenberg k m 250 mi tzs k ch kmm 220 1 72, 6 Zehr en kmk m 97 89.7 km 8 k m 73 k m 43 Sc hm k m 13 3 i lk a k m k m -04 .1 k m -1.5 4 Zern osek k m -4 1 y km - 52 k m -6 km 7 O bris k m -1-8 3 tv i k m 04 -1 k m -1 14 Kl ava k m-1 15 ry km 51 Pard -186 ub .-S emt.k m -2 28 km 237

EP

Cux h aven km 7 25, Brun s bütt k m 73 2 el km 0 69 G rau erort k m 69 7 km 6 3 60 k m 6 .5 See m 43 anns k m hö Por t ft k m 62643 Por t of Ha mb 8.8 Por t of Ha mbur g Por t of Ha mbur g Por t of Ha mbur g of Ha ur g mbur Bun t g haus k m 61 Bun th km 6 1 a 0 G ees us km 9,8 G eesth acht k 60 9,8 th ach m 586 t km 5 Sc hn k m 586 ac ke k m 579 nb ur Cum g km 4 10 Cuml osen km7 4.5 l osen 4 km 4 70 k m 4 70 k m 455 k m 423 k m 309 k m 390 Magd 63 k ebur g kmm 336 318,1 km 2 90

WHO-TEQ (pg g-1 dw)

figure_3_revised.doc

ACCEPTED MANUSCRIPT

km 259.5

Wittenberg km 214.1

km 259.5 Mulde

river Elbe: dioxin jump at Wittenberg/Magdeburg (FDS, SPM)

Magdeburg

km 318.1

100

Wittenberg

km 214.1

0

2010

2013

highlights_revised.doc

ACCEPTED MANUSCRIPT Highlights In the 1940s the Elbe was probably contaminated with dioxin from a magnesium plant. Nowadays the Elbe is contaminated from dioxin emissions from its floodplains. The dioxin patterns of the magnesium production and the Elbe are similar.

RI PT

Extreme floods do not contribute significantly to the dioxin level in the Elbe.

AC C

EP

TE D

M AN U

SC

It seems practically impossible to perform a dioxin remediation in the Elbe.