Chemical monitoring in biota: the current practice Georgia Buchmeier Norman, Expert Group Meeting, Brno,

Transcription

1 Bayerisches Landesamt für Bavarian Umwelt Environment Chemical monitoring in biota: the current practice Georgia Buchmeier Norman, Expert Group Meeting, Brno,

2 Why we do biotamonitoring? Because we want to know something about the well-being of biota or ecosystem Wetakesamples andlook at: species composition abundance of individuals age groups in the populations Chemical load in biota Chemical load in water, sediment or a passive sampling medium gives no direct information about well-being of biota

3 Chemical monitoring in aquatic biota in Bavaria fish (passive monitoring) since 1995 mussels (active monitoring) since 2000 Bavarian biota sample bank since 2004 aims: find responsible source of pollution documentation of a sucessful restauration description of trends complience of limiting values (EQS) examples for analysed pollutants: anorganic substances: Cr, Ni, Co, Cu, Zn, As, Se, Cd, Sb, Pb, Ag, Hg8 organic substances: chlorobenzene, HCB, HCBD, PCB, lindane, DEHP, methyl-triclosan (biozid-metabolit), synthetic musk 8

4 Why is fish or mussel used for monitoring of pollutants? detection limit (water concentration too low) accumulation in food chain accumulation via water and food interpretation of biological effects secondary poisoning temporal integration load in a distinct site (mussel) spatial integration (fish) concentrations in food (fish)

5 Mussel-Pollutant-Montoring mussels from poorly influenced sites(also analysed for comparison) onesizegroup exposition in spring and autumn for 6 month(active monitoring) defined sampling site definedperiodoftime pooled samples quickly results

6 Mussel-Pollutant-Monitoring (Dreissena polymorpha) exposition of 200 mussles pooledsamplesof mussels Lech

7 Mussel-Pollutant-Monitoring (Anodonta sp.) or (Unio pictorum) exposition of 10 mussels pooledsamplesof10 mussels Loisach

8 Sampling sites of Mussel-Pollutant-Montoring sampling sites Alz, Emmerting

9 Mercury in Dreissena polymorpha (years ) Alz Alz, Emmerting Hg ( mg / kg fw)

10 Methyl-Triclosan in Dreissena polymorpha (years ) Regnitz (below Nürnberg) Danub, Günzburg (below Ulm) Danub, Jochenstein (border to Austria) M-TCL ( µg / kg fw ) Isar (below Munic) Naab Donau, b. Ulm Donau Joch.st.

11 HCB (µg / kg fw) in muscle of fish in the Bavarian sampling sites All species without eal ( Median)

12 Which sampling site and method?

13 How many individuals and which species? Decisions you have to make are: takea bottomliving oran open waterspecies predatorornot how many individuals are needed for staisical analysis

14 Which investigation period (season) and age?

15 Which tissue?

16 How to mix and conservate the samples?

17 Fish-Pollutant-Montoring since sampling sites samplingevery3 years 10 individuals standardised weight annually in autumn Leuciscus cephalus(chub) in rivers Perca fluviatilis (perch) or Esox lucius(pike) in lakes muscle, liver homogenated samples nopoolsamples frozen or lyophylisated for conservation 10 years stored for retrospective study

18 Mercury in muscle of fish in 2011 Wesergebiet Thüringen Hessen Coburg Sachsen Hof Baden-Württemberg TSCHECHISCHE REPUBLIK ÖSTERREICH SCHWEIZ Bavarian Environment Mercury in muscle of chub (rivers) and perch or roach (lakes) in µg / kg fw (mean value) Eger Mercury also analysed in Dreissena EQS: < 20 µg/kg fw Rednitz µg/kg fw µg/kg fw µg/kg fw > 500 µg/kg fw Saale Steinach Sächs. Saale Rodach Itz Eger Fränk. Saale Sinn Main Röslau Weißer Main Roter Main Main Aschaffenburg Schweinfurt Wern Bayreuth Elbegebiet Main Waldnaab Haidenaab Schwarzach Naab Regen Fränk. Rezat Gr. Regen Kl. Regen Schw. Regen Ilz r. Laber G Abens Vils Ilm Kl. Vils Isar Paar Amper Donau Rott Schmutter Zusam Wiesent Regnitz Aisch Tauber Pegnitz Vils Main - Donau - Altmühlsee Kanal Altmühl Wörnitz Donau Brenz Gr. Vils Inn Mindel Günz Isen Lech Inn Iller Donau Alz Würm Isar Salzach Traun Chiemsee Saalach Tir. Achen Wörthsee Starnberger See Ammer Wertach Inn isach Königssee Lo Rothsee Altmühl Rheingebiet Würzburg Donaugebiet Waginger- Tachinger-See Simssee Schliersee Tegernsee Pilsensee Kochelsee Sylvensteinspeicher Riegsee Staffelsee Ammersee Forggensee Brombachsee Mangfall Rheingebiet Memmingen Kempten Bamberg Schwabach Ansbach Kaufbeuren Fürth Augsburg Erlangen Nürnberg Iller Walchensee Ingolstadt Amberg MÜNCHEN Landshut Rosenheim Weiden i.d. OPf. Regensburg Straubing Passau Donaugebiet Bodensee Eibsee Salzach Inn Isar Lech Rhein

19 Mercury in muscle of fish, Median ,(Min-Max) Hg(mg/kg fw) species number Hg(mg/kg fw) 0,08 (0,02 0,13) trout 7 0,41 (0,14 0,65) perch 13 eal 7 0,24 (0,13 0,39) roach 23 0,25 (0,11 0,49) Trinkwassertalsperre Mauthaus Alpsee

20 Mercury in Biota, Median ,(Min-Max) river, site species Hg (mg/kg fw) number Danub, Dillingen chub (muscle) 0,07 (0,04 0,27) 17 Danub, Dillingen eal (muscle) 0,20 (0,11 0,59) 28 Danub, Günzburg Dreissena 0,01 (pooled samples) Lech, Feldheim chub (muscle) 0,29 (0,10 0,78) 24 Lech, Feldheim eal (muscle) 0,53 (0,24 1,68) 19 Lech, Feldheim Dreissena 0,02 (pooled samples) Danub Lech

21 Mercury in muscle of fish ( ) Bavarian Environment fish of all sites N = 184 Eal N = 127 Chub N = 20 Barbel N= 67 Bream N = 28 Roach N = 39 Pike Hg ( mg / kg fw)

22 Hexachlorbenzene in muscle of fish ( ) Median below determination limit N = 184 Aale eal N = 127 Aitel, Döbel chub N = 20 Barben barbel Brachse, N= 67 Brassen bream N = 28 Rotaugen roach N = 39 Hechte pike HCB ( µg / kg fw) fish of all sites

23 Hexachlorbenzene in liver of fish ( ) N = 180 eal N = 126 chub N = 18 barbel N= 66 bream N = 28 roach N = 39 pike HCB ( µg / kg fw)

24 N=180 alle Stellen N=7 Wörnitz N=9 Main, Schweinfurt N=11 Main, Erlabrunn N=9 Fränkische Saale N=7 Main, Rothenfels N=6 Main, Kleinheub. N=6 Main, Kahl PCB 153 ( µg / kg fw ) *** * *** ** *** PCB 153 in liver of eal ( ) Bavarian Environment * p < 0,05 ** p < 0,01 *** p < 0,001

25 PCB 153 in liver of barbel ( ) ** Bavarian Environment ** p < 0,01 N =66 alle Stellen N=6 Wörnitz N=5 Donau, Deg. N=7 Inn, Simbach N=7 Donau, Joch. N=6 Main, Schwf. PCB 153 ( µg / kg FG )

26 Conclusions Biotamonitoring is a good instrument for assesment of ecosystems Biota incorporate pollutants from water and from food Biota integrateovera time period Showing differences between monitoring sites Showing differences between species Showing trends Biota-samples have to be standardised as good as possible in a sampling-programm Biota-samples should be described (age, fat, weight8) for interpretation of data