1. Chris Cooper and Frank Van Assche International Zinc Association
Accounting for bioavailability with poor data: options and opportunities
Chris Cooper and Frank Van Assche
International Zinc Association 1

2. Quality of bioavail. parameters
Matched/coupled bioavail. parameters are preferred.
Local data on same water body (50P or Ave.)?
Near the Me sampling point.
EU data from general EU datasets.
Providing specific regional info. 2

3. Pros and cons Matched/coupled data: This is obviously ideal.
Most accurate assessment.
Are all data actually available?
According to JRC, only one country has these matched data. 3

4. Matched data – data collection or sampling issue?4

5. Pros and cons Local data:
Information within the same waterbody, or surrounding waterbodies = local concentration.
How do we make this approach acceptable at a regulatory level?
What are the temporal and spatial limits? 5

6. Pros and cons EU data: FORum of European Geological Surveys (FOREGS):
Consistent coverage over EU.
Consistent sampling and analysis.
Single ‘snap shot’ in time.
‘Old’ data.
Water Information System for Europe (WISE):
Member State submitted data.
Large dataset, network, interface, etc. established.
Aggregated data.
Unsure of data quality. 6

7. FOREGS, 2005 (http://weppi.gtk.fi/publ/foregsatlas/ForegsData.php)
Some sampling info….
160 x 160 km cells:
5 randomly generated points = 5 nearest small water basins.
Centre of the cell = country.
One team sampled all sites in each country during one field season:
Between 1997 – 2001.
Winter and early spring. 7

8. FOREGS, 2005 (http://weppi.gtk.fi/publ/foregsatlas/ForegsData.php)8

9. WISE (http://water.europa.eu)
WISE = European Commission (Directorate-Generals for Environment, Joint Research Centre and Eurostat) + European Environment Agency.
The main objectives of WISE are:
To provide a single entry point to access data (provided by mainly Member States).
To assess and compare environmental status (river basins).
To check the compliance with European water legislation.
To asses the effects and the effectiveness of the EU water policy. 9

10. WISE vs FOREGS Is using the 50P from FOREGS acceptable?
Can we take this a step further? 10

11. BioF’s for each Member State22
BioF’s for each Member State
0,00-0,10
0,11-0,20
0,21-0,30
0,31-0,40
0,41-0,50
0,51-0,60
0,61-0,70
0,71-0,80

12. FOREGS, 2005 (http://weppi.gtk.fi/publ/foregsatlas/ForegsData.php)12

13. DOC: the Baltic states - Lithuania13

14. pH
S. LT.: 7,7
N. LT.: 8,0
Ca (mg/l)
S. LT.: 110
N. LT.: 120 14

15. DOC: the Baltic states - Lithuania
Possible regional [DOC] and other parameters…
Region
DOC mg/l
Southern Lithuania
14,0
Northern Lithuania
8,5 pH
Ca mg/l
BIOF
7,7
110
0,12
8,0
120
0,18
(LT WISE, 2012)
(LT FOREGS, 2005)
DOC (mg/l)
Min.
Mean
Max.
Median
11,5
14,9
24,7 Nd
90P
10,6
13,0
17,8
50P
9,2
9,8
11,2
10P
6,8
8,4
9,4
Ave.
8,8
10,4
12,7
No. of samples 14
FOREGS River
DOC mg/l
Max.
50,2
90P
14,8
50P
10,8
10P
7,2
Ave.
13,5
No. of samples 14 15

16. DOC: Finland
Finland has uniformly high DOC. 16

17. DOC: Finland 17

18. pH
Finland: 6,5
Ca (mg/l)
Finland: 4,2 18

19. Possible regional [DOC] and other parameters…
DOC: Finland
Possible regional [DOC] and other parameters…
Region
DOC mg/l
North Finland
8,0
Rest of Finland
20,0 pH
Ca mg/l
BIOF
6,5
4,2
0,34
0,18
(FI FOREGS, 2005)
FOREGS River
DOC mg/l
Max.
71,9
90P
39,9
50P
17,4
10P
9,0
Ave.
22,4
No. of samples 65 19

20. Quality of bioavail. parameters
Matched/coupled bioavail. parameters are preferred.
Local data on same water body (50P or Ave.)?
Near the Me sampling point.
EU data from general EU datasets.
Providing specific regional info. 20