Copper complexation in English Rivers

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Chemical Speciation and Bioavailability (2000), 12(1)

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Copper complexation in English Rivers Michael Gardner* Eleanor Dixon and Sean Comber WRc-NSF, Henley Road, Medmenham, Marlow SL7 2HD, UK

ABSTRACT

Data for copper complexation capacity (CC), determined by cathodic stripping voltammetry, are presented for 36 English rivers. Values for CC were between 40 and 500 nM. No predictive relationship between major water quality parameters and CC was found. A comparison of determinations made on the same water bodies over several years points towards consistency of CC with time. It is concluded that, in river waters of a wide range of types, forms of copper complexed by organic matter predominate substantially over free or inorganic forms of the metal. Keywords: copper, metal speciation, river water, voltammetry

INTRODUCTION Although the importance of copper complexation in marine waters has been discussed extensively in the scientific literature over the past twenty years, relatively little data have been reported for the freshwater environment. Studies of copper speciation in fresh waters or effluents have largely dealt with individual locations or case studies. Little information on a generalised survey basis is available. Buykx et al. (1999) report complexation capacity data in the range 100–500 nM for 14 European rivers; Antello et al. (1998) studied seasonal variation of copper speciation in two Spanish rivers. This paper is intended to add to the data on copper complexation in freshwaters. Its specific aims are: to present a body of internally consistent data for copper complexation in English river waters; and, to provide a comparison of determinations made on the same water bodies over several years. Copper complexation by naturally occurring organic matter has been studied widely. The motivating factors for this interest are:

*To whom correspondence should be addressed. Fax +44 1491 636501; E-mail: [email protected]

• copper is relatively toxic to aquatic life; • the variety of applications of copper is such that the potential for some level of contamination is almost universal; and, • it has been established that organically complexed forms of copper are substantially less toxic than the free metal ion or inorganically associated species (i.e. Cu2+, Cu(CO3)22–, Cu(OH)+ etc.). This difference in toxicity has been linked to differences in bioavailability which in turn have been explained in terms of the lower chemical reactivity of organic forms, compared with the reactivity of inorganic species. The two principal factors that define the organic complexation of a metal in water are the effective total ligand concentration and the conditional stability constant, K′lig, of the metal–ligand complex in the water matrix of interest. The ligand concentration represents the capacity of the water to complex the trace metal, hence its alternative description as ‘complexation capacity’ (CC). K′lig is an expression of the strength of the metal–ligand complex: K'lig =

[ML] [M' ][L' ]

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Copper complexation in English Rivers

where [ML] is the measured concentration of metal ligand complex. [M′] is the concentration of uncomplexed metal ion detected by the analytical technique employed – labile or notionally the inorganic fraction, [L′] represents the concentration of uncomplexed ligand. Complexes of higher K’lig values (>107) have been shown to be substantially less bioavailable and, consequently, to be of lower toxicity to aquatic life (Borgman, 1983, Allen et al., 1980, Allen and Hansen, 1996, Erickson et al. (1996)). This distinction has been recognised in the way that European Union (EU) water quality standards have been defined (but not necessarily in how such standards are applied, see below). Current interpretations of EU legislation (Gardiner and Mance, 1984) acknowledge the influence of speciation on copper toxicity by inclusion of a provision that defines toxicitybased limits for copper concentrations in surface water may be exceeded ‘where organic complexation is present’. Proposed Australian and New Zealand water quality standards also recognise the importance of speciation (ANZECC, 1999). Speciation-related provisions have not yet found widespread application largely because of lack of data concerning complexation. However, both regulatory bodies and effluent dischargers are beginning to recognise that regulation on the basis of total or total dissolved metal concentrations is unsound. Continuation of the principal current approach, based on dissolved metal, leaves the regulator in the untenable position of trying to enforce quality standards that are not supported either by scientific evidence or by field data. This approach also places the municipal or industrial or discharger under a costly obligation to control sources of contamination, for little prospect of environmental gains. It is hoped that a national survey of CC might provide background data against which future regulatory policy might be framed. METHODOLOGY The cathodic stripping voltammetry (CSV) procedure adopted for determination of electrochemical speciation by complexation titration is summarised below. This approach has been used in essentially the same form (by the same research group) at our laboratory since the early 1990s. This level of internal consistency prompted the temporal comparisons shown below. Samples were buffered at a pH value within 0.2 of their natural values in order that loss of carbon dioxide during nitrogen purging did not change the sample pH value. For example, for a sample of pH 7.8, 1 M EPPS buffer (N-2-hydroxyethylpiperazine-N′-3-propane sulfonic acid – a biological buffer of minimal complexing capacity, pKa 8.00) was prepared in 0.5M ammonium hydroxide such that an addition of 150 L buffered a 15 mL sample of river water to a value of

7.80.2. EPPS was used in the pH range 7.6–8.2, PIPES (piperazine-NN-bis-2-ethanesulfonic acid, pKa 6.8) in the range 6.4–7.6. Samples of pH less than 6.4 needed to be addressed by the different technique of anodic stripping voltammetry. The buffer pH was shown to be maintained during the course of a complexation titration. The working copper standard solution at a concentration of 5 mg L was prepared from commercially available stock solutions (Merck Spectrosol); it was adjusted to a pH value of between 2.5 and 3. A 0.0025 M solution of catechol was prepared freshly each day. Differential pulse cathodic stripping voltammetric measurements were made using a Metrohm hanging mercury drop electrode interfaced with a Metrohm 626 polarograph or Metrohm 757 Computrace. The reference electrode was Ag/AgCl, satd. KCl. A 15 ml aliquot of sample was pipetted into a PTFE polarographic cell and buffered with 150 l of EPPS buffer. The sample was purged with nitrogen for 7 minutes and 60 l of catechol solution was added to give a concentration of 1 10–5 M. (N.B. larger quantities of catechol are added to samples of pH lower than 7.7–8.0 to maintain the same competitive effect – the same concentration of ionised catechol ) The sample was purged and stirred for a further 3 minutes to allow equilibration between the added ligand and naturally occurring copper species. A new mercury drop was formed and an adsorption potential of 0.0V was applied for 50 s with stirring. Following an unstirred quiescent period of 10 s, a potential scan was initiated (negative direction, scan rate 10 mV s–1, pulse height 50 mV, pulse rate 2 s–1) and the copper reduction wave recorded at ca –1.05 V. An addition of copper equivalent to 5–10 g l–1 was made and the measurement cycle was repeated (after 3 min equilibration). Further incremental additions of copper, up to 80 g l–1 (or where non-linearity was observed), were made with successive measurement of the CSV response until a titration curve was generated. The apparent complexation capacity and notional conditional constant for equilibrium between ligands and copper was determined by the method of Rusic (1982). The power of the technique to detect the range of potentially complexing ligands in natural waters is dependent on the extent to which the added catechol competes with the weaker of these ligands. The chosen catechol concentration represents a compromise between the need to add sufficient catechol to achieve adequate analytical sensitivity and the desire to minimise the competitive effect of catechol, in order to detect the full complement of ligands. To assess the comparability of the method with techniques used by other workers, several samples were analysed both as above and by the widely used technique of anodic stripping voltammetry. For ASV, the same equipment and experimental conditions were used, but with a stirred plating phase

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Figure 1 Comparison of complexation capacity determined by ASV and CSV.

of 50s at –0.4V and an anodic sweep to +0.1V.) The ASV technique involves no added competitor ligand and is therefore less ‘tuneable’ than CSV with respect to ligands of different K′lig value.

ability level. This is an indication of consistency of CC over time, but further investigations are required to provide confirmation of this conclusion and to assess the influence of seasonal factors.

RESULTS

DISCUSSION

The comparison between the CSV and ASV techniques is shown in Figure 1. There is a large measure of correlation (R2=0.93) between the two data sets, but it appears that the CSV technique detects approximately 0.7 of the CC determined by ASV (CCASV = 1.4 CCCSV). This indicates that the measures of CC obtained by the CSV technique may not include some of the weaker ligands accessed by ASV. As such, the data presented below might be considered to be conservative estimates of the total potential CC. Data for complexation determined by the above technique are presented in Table 1. Sampling locations are shown in Figure 2. Measurements of CC have been made at the same locations over an interval of several years. The comparison of these results are shown in Figure 3. The slope of the regression of one set of data on the other is close to unity and the correlation coefficient (0.72) achieves significance at the 0.01 prob-

For more recent data, some background water quality data are provided. Absorbance at 400nm was determined as in indication of humic/fulvic acid levels. No significant correlations were found between CC and pH, conductivity, absorbance at 400nm or alkalinity. This confirms the finding of Buykx et al. (1999). The wide variety of types of potential ligands in water – proteins, amines, carboxylic acids, polysaccharides, amino acids etc. – means that it is unlikely that the influence of humic substances is as important as it has been reported for media such as soils. It is important to recognise this, in view of the widely-held view that humic substances are largely responsible for trace metal complexation. The value of K′lig is critical to the attempt to estimate the relative proportions of labile (inorganic) copper and organically complexed metal. The value of K′lig obtained from the complexation titration suffers from

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Table 1 Copper Complexation Capacity in English Rivers Site River no.

1 2 3

Date

pH

R Severn, Minsterworth, Jul–88 7.4 Gloucester R Wharfe, Tadcaster, Feb–90 ND N Yorks Whiteadder Water Jun–90 9 E Ord, Northumberland

Complexation Dissolved % inorg Colour capacity nM Cu nM of total + mAU / 4cm* 196

43

318

14

191

52

Conductivity Alkalinity S/cm mEquiv Reference

Apte et al., 1990a Apte et al., 1990b Gardner and Ravenscroft 1991b Gardner and Ravenscroft 1991b Gardner and Ravenscroft 1991b Gardner and Ravenscroft 1991a Gardner and Ravenscroft 1991a Gardner and Ravenscroft 1991a Gardner and Ravenscroft 1991a

4

R Tweed, E Ord, Northumberland

Jun–90 8.9

258

65

5

R Tweed, Norham, Northumberland

Jun–90 8.5

328

60

6

R Great Ouse, Wiggenhall, Norfolk

Dec–90 7.8

494

22

7

R Great Ouse, Wiggenhall, Norfolk

Jan–91

7.9

515

19

8

R Hull, Beverley E Yorks

Jun–91 7.8

271

6

9

R Hull, N Hull, E Yorks

Jun–91 7.8

235

15

Dec–92 7.6

472

54

Dec–92 Dec–92 Dec–92 Dec–92 Dec–92 Dec–92 Dec–92 Feb–96

7.7 7.7 7.6 7.6 7.7 7.6 7.7 7.5

409 394 504 472 441 488 457 143

69 66 55 52 99 90 93 33

Feb–96 7.6

139

19

Nov–99 7.9 Nov–99 7.8

46 391

14 44

10 1

33 45

Jan–00 Jan–00

7.76 3.68

332 438

45 194

1 1

57 507

820 77

6.00 –0.2

Jan–00

3.88

189

31

2

285

80

–0.1

Mar–00 7.28

88

13

4

13

75

0.27

Mar–00 7.43

85

16

4

14

85

0.30

May–00 7.6

91

35

4

150

327

2.47

May–00 7.8 May–00 7.8

328 384

49 99

1 1

51 75

368 708

2.78 5.33

Feb–90 7.3

176

25

10

R Churnet, 7 sites over 10 miles between Leek and Rocester, Staffs 11 R Churnet, Staffs 12 R Churnet, Staffs 13 R Churnet, Staffs 14 R Churnet, Staffs 15 R Churnet, Staffs 16 R Churnet, Staffs 17 R Churnet, Staffs 18 R Tyne, Wylam, Northumberland 19 R Tyne upstream of R Derwent 20 R Test, Andover, Hants 21 R Gt Stour, Ebbesfleet, Kent 22 R Trent, Dunham, Notts 23 Burbage Brook, Hathersage, Derbys 24 Sheephouse Brook, Hathersage, Derbys 25 R Barle, Withypool, Somerset 26 R Exe, Exford, Somerset 27 R Morda, Oswestry, Shropshire 28 R Wye, Buxton, Derbys. 29 R Trent Burton on Trent, Staffs historic comparisons 30a R Ouse, Selby, N Yorks

Apte et al., 1990b

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Table 1 Copper Complexation Capacity in English Rivers (continued) Site River no.

Date

31a R Derwent, Barmby, E Yorks 32a R Aire, Beal, N Yorks

Feb–90 nd

198

14

Feb–90 nd

331

63

Feb–90 nd

323

55

May–91 7.2

141

93

May–91 7.7

425

135

May–94 7.8

372

31

Jan–00 Jan–00

7.81 7.99

79 101

18 13

5 3

185 31

244 623

2.14 6.75

Jan–00 Jan–00

7.7 7.76

424 384

64 40

1 1

97 100

515 726

2.78 4.15

Jan–00

7.74

191

36

3

146

290

2.56

Jan–00 Jan–00

7.99 7.8

422 180

55 35

1 2

27 60

944 650

7.69 4.60

33a R Don, Fishlake, S Yorks 34a R Ouse, Boothferry, E Yorks 35a R Trent, Althorpe, Lincs 36a R Thames, Medmenham, Bucks 30b R Ouse, Selby, N Yorks 31b R Derwent, Barmby, E Yorks 32b R Aire, Beal, N Yorks 33b R Don, Fishlake, S Yorks 34b R Ouse, Boothferry, E Yorks 35b R Trent, Althorpe, Lincs 36b R Thames, Medmenham, Bucks

pH

Complexation Dissolved % inorg Colour capacity nM Cu nM of total + mAU / 4cm*

Conductivity Alkalinity S/cm mEquiv Reference Apte et al., 1990b Apte et al., 1990b Apte et al., 1990b

ND = not determined; * +% inorg. Copper expressed as a proportion of the total dissolved copper concentration, absorbance at 400nM measured as an indicator of colour.

two serious limitations: (a) it represents an ‘average’ value for all the natural ligands of true K′lig greater than a threshold level determined largely by the precision of the analytical technique; and, (b) the measured value is negatively biased. Essentially, the detection threshold corresponds to the point at which it is possible to detect the difference between non-complexed metal and total metal, when the degree of complexation is small. Limitation (a) has been discussed at length by Apte et al. (1990b) who estimated that the detection threshold for this particular technique is for complexes of log K′lig greater than 8.5–9. Limitation (b) has been investigated more recently by Dixon et al. (1999) whose computer simulations suggest that the negative bias for log K′lig values of 8–9 is between 1 and 2. The measured logaverage K′lig of 7.8 (for data obtained in 2000, the range of measured log K′lig was 6.8–8.8) is consistent with these predictions of a true log K′lig of 9 and negative bias in the estimated log K′lig of approximately 1.2. Examination of the shape of titration curves for these water samples indicated (with one exception where industrial discharges of stronger articficial complexants were likely to have been present) that there are no substantial differences in the underlying average K′lig. Hence it may be assumed that a single K′lig based on the detection capabilities of the technique might be appropriate. A value of log K′lig of 8.5 has been used

for data in Table 1 in calculating the proportion of inorganic copper. Given the issues discussed by Apte et al. (1990b) and Dixon et al. (1999), the calculated % inorganic fraction is a likely to be a worst-case estimate of the proportion of potentially most toxic inorganic forms of copper. CONCLUSIONS (1) The copper complexing capacity (CC) of a variety of surface waters, ranging from acid upland streams to large lowland rivers, over a wide geographical area, has been determined. Values for CC are between 40 and 500 nM. (2) In all cases, complexation capacity exceeds the concentration of dissolved copper. Calculation of copper speciation indicates that forms of copper complexed by organic matter predominate substantially over free or inorganic forms of the metal. (3) The widely-held view that humic substances are largely responsible for trace metal complexation, does not appear to be true for copper in river waters (4) It is most unlikely that CC or copper speciation can be predicted on the basis of general water quality parameters such as alkalinity, colour, conductivity,

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Figure 2 River sampling locations.


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CC 90/94 nM Figure 3 Complexation capacity – temporal comparison of complexation capacity – determined in 2000 versus data for the same locations as in 1990–1994. Solid line is the 1:1 line, CC is complexation capacity in nM. Dotted line is the linear regression line of y on x (formula: y =1.01x +28.73). Data refer to the data in Table 1 obtained for the temporal comparison between January 2000 and 1990–94.

pH etc. This leads to the conclusion that some form of practical assessment of CC is required, if the speciation of copper in natural waters is to be determined. (5) Comparison between CC measured several years ago and current determinations for the same sites suggest consistency of CC levels over time, but further investigations are recommeded to confirm this conclusion and to assess the influence of seasonal factors. REFERENCES Allen, H.E., Hall, R.H. and Brisbin, T.D. 1980. Metal speciation. Effects on aquatic toxicity. Envir. Sci. Technol., 14, 441–443. Allen, H.E. and Hansen, D.J., 1996. The Importance of Trace Metal Speciation to Water Quality Criteria. Water Envir. Research, 68, (1), 42–54.

ANZECC 1999. http://www.mfe.govt.nz/issues/water/ anzecc_guide.htm Borgmann. U. 1983. Metal speciation and toxicity of free metal ions to aquatic biota. In Aquatic toxicology J O Nriagu (ed.). Wiley Interscience, New York. Buykx, S.E.J., Cleven, R.F.M.J., Hoegee-Wehmann, A.A. and van den Hoop, M.A.G.T. 1999. Trace metal speciation in European River waters. Fres. J. Analyt. Chem., 363 599–602. Antello, J.M., Arce, F. and Penedo, F.J. 1998. Effect of seasonal changes on the complexing of Cu(II) by dissolved organic matter in river water. Water Res., 32 (9): 2714–2720. Apte, S.C., Gardner, M.J. and Ravenscroft, J.E. 1990a. Copper Speciation in the Severn Estuary. Mar. Chem., 29, 63–75. Apte, S.C., Gardner, M.J., Ravenscroft, J.E. and Turrell, J.A. 1990b. Examination of Copper Complexation in Natural Waters using a Combination of Cathodic Stripping

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Voltammetry and Computer Simulation. Anal. Chim. Acta, 235, 287–299. Dixon, E. M., Gardner, M. J. and Parry, S. J. 1999. Optimised Design for Complexation Capacity Titrations. Chem. Spec. Bioavail., 11 (2) 51–56. Erickson, R.J., Benoit, D.A., Mattson, V.R., Nelson, H.P., and Leonard, E.N. 1996. The Effects of Water Chemistry On the Toxicity of Copper to Fathead Minnows. Envir. Toxicol. Chem., 15 (2): p. 181–193. Gardiner, J. and Mance, G. 1984. United Kingdom water quality standards arising from European

Community Directives. Water Research Report, TR 204. Gardner, M.J. and Ravenscroft, J.E. .1991a. Copper Complexation in Rivers and Estuaries: Two Studies in NE England. Chemosphere 2 3, 695. Gardner, M.J. and Ravenscroft, J.E. 1991b. The Range Copper Complexing Ligands in the River Tweed. Chem. Speciat. Bioavail., 3 , 22. Ruzic, I. 1982. Theoretical aspects of the direct titration of natural waters and its information yield for trace metal