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Suggestions for improved WFD water quality monitoring programs

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Presentation on theme: "Suggestions for improved WFD water quality monitoring programs"— Presentation transcript:

1 Suggestions for improved WFD water quality monitoring programs
Eric de Deckere, Joop Bakker, Werner Brack, Dick de Zwart, Edwin Foekema, Marja Lamoree, Pim Leonards, Isabel Munoz, Claus Orendt, Bert Van Hattum, Sander Van Vliet, Georg Wolfram & Peter Von der Ohe

2 ? ? Surveillance & operational monitoring Effective measures
Surveillance & operational monitoring ≈ status & trend monitoring focusing on chemical and ecological status WFD classification Chemical status ≥good ≤ moderate ≤ moderate ≥good Ecological status ≥good ≤ moderate ≥good ≤ moderate Effective measures No action needed Improve chemical status ? Improve chemical status ?

3 Status/trend monitoring: Zenne
Can we identify the relevant stressors with the current monitoring programmes?

4 Identification of relevant stressors
(De Zwart et al., 2009) Lack of specific data, eg. sediment related pollutants and habitat, results in a big fraction unknown stress

5 dominating stressor can change
Identification of relevant stressors Example: Critical prometryn concentrations for flagellate population under nitrogen limitation dominating stressor can change (Bontje et al., 2009)

6 Total of 27 pollutants with TU > 0.01!  only 6 Priority pollutants
Assess monitoring data with ‘MODELKEY’ tools Total of 27 pollutants with TU > 0.01!  only 6 Priority pollutants

7 TUmax algae Danube top 15 Assess monitoring data with ‘MODELKEY’ tools
no Stream site ID year n TUmax Compound conc. (µg l-1) 1 Danube 108 1999 2.0 -0.03 4,4'- DDT 2.67 2 098 1997 -0.26 1.59 3 Sulina 097 1.7 -0.36 1.25 4 095 -0.38 1.20 5 070 2.3 0.98 6 Arges 087 1.5 -0.41 1.11 7 064 1998 1.3 -0.51 0.88 8 089 -0.52 0.93 9 Morava MO1 2007 16.0 -1.12 terbuthylazine 0.245 10 MO2 -1.40 0.128 11 080 2000 1.0 -1.47 0.10 12 016 15.0 -1.80 0.050 13 Sio 042 12.0 -1.77 0.054 14 050 14.0 -1.70 0.063 15 044 3.0 0.05

8 Number of measured chemicals

9 Contaminants in the sediment have to be considered
Analysis of monitoring data AA-EQS exceeded AA-EQS not exceeded A list of chemicals is always limited, and the list will influence the identification of the stressor in the present status and trend monitoring Contaminants in the sediment have to be considered (De Zwart et al., 2009) The number of compounds that can be analysed over the different matrices is the limiting factor; Effect monitoring should be included in an early stage (Bron: De Zwart et al., 2007)

10 Surveillance & operational monitoring
Requires adequate monitoring Monitoring 1900-WFD

11 DEFINITION MONITORING (UN/ECE)
A process of repetitive observing (~ trend analyses) for defined purposes (~ policy) of one or more elements of the environment (~ environmental themes/compartiments) according to pre-arranged schedules in space and time (~ monitoring strategy) using comparable methods for environmental sensing and data collection (~ development assessment methods) providing information on present state and past trends in environmental behaviour (~ reporting) A tool to prepare, assess and evaluate a program of measures Cause-effect links should be established

12 ? ? Surveillance & operational monitoring Effective measures
Surveillance & operational monitoring ≈ status & trend monitoring focusing on chemical and ecological status WFD classification Chemical status ≥good ≤ moderate ≤ moderate ≥good Ecological status ≥good ≤ moderate ≥good ≤ moderate Effective measures No action needed Improve chemical status ? Improve chemical status ?

13 ? Effective measures WFD classification ≤ moderate ≤ moderate ≥good
Bioavailability Chemical status Ecological status Internal response concentration External Community development Population Individual effect ECOLOGY TOXICOLOGY CHEMISTRY WFD classification ≤ moderate ≤ moderate ≥good ≥good Effective measures Improve chemical status ?

14 water managers perspective
Bioavailability Chemical status External concentration Internal response Ecological status Community development Population Individual effect ECOLOGY TOXICOLOGY CHEMISTRY Chemical analysis In-vitro assays Biometric extracts In-vivo biomarkers In-vivo bioassays Population indices Community indices Tools water managers perspective Poor ecological status Are toxicants involved? Identify key toxicants Take cost effective measures

15 Genus composition of macro invertebrates in the Schijn
Identification of cause-effect relationship Genus composition of macro invertebrates in the Schijn

16 Identification of cause-effect relationship
For the first test, we choose the samples, where reference and polluted sites had the bigest difference, which was, as you may remember at the Elbe Most and Jirkov and at the Scheldt Rundvoort and Eenhoorn. (Bron: Schmitt et al., in prep.)

17 Identification of cause-effect relationship
Field sediments Extraction/Fractionation Laboratory culture of Potamyrgus antipodarum Spiked artificial sediment Endpoint reproduction 0.2 mm embryo with shell embryo without shell Sediment contact test Endpoint growth 4 mm We used the same field sediments as before, extracted all the compounds with Soxhlet and spiked artificial sediments with a solution of those extracts. Then we took the same snails from the culture together with the spiked sediments and reconstituted water in beakers and followed the same procedure as in the previuos test, where we hat growth and reproduction as endpoints. (Bron: Schmitt et al., in prep.)

18 Identification of cause-effect relationship
Cause-effect relationships between ecological status and chemical compounds can be made, the results of MODELKEY confirm this, but the tools should be further established. Fractionation studies (EDA) helped to identify the co mpounds that are responsible for the lack of certain species at the hot spot This graph shows the results of the sediment extraction test after 28 days of expoure. In this experiment, beside a control, also a solvent control had to be carried out, because the extractions were solved in dichlormethane and we had to be sure that there is no impact of Dichlormethane on the snails. Apparently there was no impact of the solvent as you see by looking at this two bars, but surprisingly we see a totally different picture for the samples than in the experiment before. We now have a decrease in reproducton at the polluted sites which is almost obvious at the Scheldt but significant fo the Elbe. Those results show, that due to the higher bioavailability of compounds in the artificial sediment the effects are changing enormously and we now have to find out, which group of substances courses which effects.

19 Conclusions Current status and trend monitoring programs are not adequate to identify the relevant stressors Modelkey tools can be used to identify main stressors and/or key pollutants The relation between sediments, suspended solids, water and biota is not well identified, but it is clear that the role of sediments is underestimated and needs to be addressed more in further research Investigative monitoring should be focused on establishing the cause-effect link to be able to develop an adequate program of measures Ecotoxicologal tests, TIE and EDA like tools, such as developed in Modelkey, are useful tools, however a lot of these tools are still under development and there are clear research needs to be able to establish this cause-effect link

20 THANK YOU Ziet er goed uit, wel benieuwd naar conclusies

21 Responsible Substance(s)
WFD classification Chemical status ≥good ≤ moderate ≤ moderate ≥good Improve chemical status Monitoring Ecological status ≥good ≤ moderate ≥good ≤ moderate In Vivo Bioassays Biomarkers OK In Vivo Bioassays Biomarkers No effect Optional Effects are compensated Effect Effect In-vitro assays EDA Identify & Remove Responsible Substance(s) Other stressors than chemicals (mainly) responsible No effect


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