Complexation of copper by aquatic humic substances from different environments

The Science of the Total Environment, 28 (1983) 65--76 Elsevier Science Publishers B.V., Amsterdam -- Printed in The Netherlands

65

COMPLEXATION OF C O P P E R BY AQUATIC HUMIC SUBSTANCES FROM DIFFERENT EN VIRON MEN TS

DIANE M. McKNIGHT) GERALD L. FEDER) E. MICHAEL THURMAN) ROBERT L. WERSHAW U.S. Geological Survey, Denver, Colorado, USA 3OHN C. WESTALL Oregon S t a t e U n i v e r s i t y , Corvallis) Oregon, USA

ABSTRACT The copper-complexing properties of aquatic humic substances isolated from eighteen different environments were characterized by potentiometric titration) using a cupric ion selective electrode.

-Potentiometric data were analyzed using FITEQL, a computer

program for the determination of chemical equilibrium constants from experimental data. All the aquatic humic substances could be modelled as having two types of Cu(il)-binding sites: one with K equal to about 106 and a concentration of 1.0 _+ 0.4 x I0 -6 M(mg C) - I and another with K equal to about I0 g and a concentration of 2.6 + 1.6 x I0 -7 M(mg C)- I . A method is described for estimating the Cu(ll)-binding sites associated with dissolved humic substances in natural water based on a measurement of dissolved organic carbon) which may be helpful in evaluating chemical processes controlling speciation of Cu and bioavailability of Cu to aquatic organisms.

INTRODUCTION A current environmental concern is the effect of trace-metal inputs on aquatic ecosystems.

Copper, which is listed as a priority pollutant by the U.S. Environmental

Protection Agency) is of particular importance in this regard and has been studied intensively. Several researchers have shown that toxicity of Cu is more closely related to the concentration of the Cu(ll) ion and not to the total concentration of Cu [ 1,2 ].

For

this reason, study of the processes controlling chemical speciation of Cu has been an important part of the overall study of the effect of Cu on aquatic ecosystems. The major processes that control the chemical speciation ol Cu in natural waters are: precipitation, formation of complexes with inorganic or organic ligands) and adsorption by particulate material.

These processes can be affected by the concentration of Cu, pH

alkalinity) and concentration of Cu-binding sites associated with dissolved organic material and suspended particulates. In general) precipitation of Cu as tenorite (CuO) or malachite (Cu2(OH)2CO3), and formation of inorganic complexes (CuOH +, Cu2(OH)2 2+, 0048-9697/83/$03.00

© 1983 Elsevier Science Publishers B.V.

66 CuCO3, Cu(CO3)22-, etc.) will become more important with increasing pH, alkalinity and Cu concentration. Organic complexation generally w i l l be important at the range of pH (6 to 8) and dissolved organic carbon (DOC) concentration (2 to 7 (mg C)L -I) typical of lakes and streams. Adsorption by particulate material w i l l be important in surface waters with significant concentrations of suspended material, such as some large rivers. Aquatic fulvic acid, the acid-soluble fraction of humic substances, is the major fraction of the dissolved organic material in natural waters.

Mantoura and others [ 3 ]

concluded that 90~ of the Cu is compiexed by dissolved humic substances in an average river water. Copper that is complexed by humic substances generally is not available to aquatic organisms [4 ]. In a field study of the CuSO 4 treatment of Mill Pond Reservoir in Burlington, Massachusetts, McKnight [ 5 ] found that the added Cu was complexed by dissolved humic substances, and that the response of the phytoplankton assemblage was determined by the Cu-ion concentration, which was an order of magnitude less than the concentration of the Cu-humic complex. In this paper, we present chemical equilibrium data for Cu(II) complexation by fulvic acids isolated from different aquatic environments.

From these equilibrium data, we

develop a simple method of estimating Cu(II)-complexing properties of fulvic acids in natural waters from concentration of DOC. With this estimate and the concentration of dissolved Cu, a chemical-equilibrium calculation including precipitation, inorganic complexation and adsorption on particulates can be performed with a geochemical model such as MINEQL [ 6 ] , to calculate the cupric ion activity in waters where the cupric ion activity can not be directly measured.

METHODS Isolation of aquatic fulvic acids The aquatic fulvic acids used in this study were isolated with XAD-8* macroporous resin, as described by Thurman and Malcolm [ 7].

The ash content of the freeze-dried

H+-saturated fulvic acids was 2%or less and no significant Cu contamination was detected.

The aquatic fulvic acids were isolated from samples collected from rivers,

streams, lakes, wetlands, and two aquifers. The DOC concentrations, percent fulvic acid, and brief descriptions of the samples are given in Table I. Carboxylic and phenolic functional groups are probably important in the Cu(ll)complexing properties of fulvic acid. The fulvic acid samples studied here had carboxylic acid concentrations ranging from 3.2 to 6.3 meq g - l , and phenolic group concentrations ranging from 0.6 to 3.8 meq g - l as measured by titration to pH 7 for carboxylic acids and to pH

I0 and doubled for phenolic acids (E.M. Thurman, U.S. Geological Survey,

unpublished data). These concentrations of functional groups bracket the concentrations generally reported for aquatic fulvic acids. * Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey.

67 TABLE I Description of source of fulvic acid samples

Source of Sample

Dissolved Organic Percent Carbon , Fulvic (mg C)L - I Acid

Rivers Shawsheen River

5.5

50

O g e e c h e e River

8.1

53

Ohio River

3.2

59

Missouri River

3.2

41

South Platte River

--

Bear River

2.9

51

Como C r e e k

6.0

65

Deer C r e e k

0.8

50

Hawaiian River

3

40

Lakes Black Lake

8.3

60

Island Lake

30

30

Brainard Lake

3.2

30

Merril Lake

1.0

43

Wetlands Suwannee River

32

80

Hawaiian Marsh

I0

50

Ground Waters Yuma Canal Yuma C a n a l (chlorinated) Biscayne aquifer

3.6

33

3.4

21

15

53

Description Small river in eastern Massachusetts that drains swamp deposits and flows into the Merrimack River Small river draining Piedmont sampled near Grange in central Georgia Major river draining east central United States, sampled at Cincinnati, Ohio Major river draining north central United States, sampled at Sioux City, Iowa River in Colorado carrying water from Dillon Reservoir to water t r e a t m e n t plants in Denver, Colorado Small stream in Rocky Mountains near Yampa, Colorado Small stream in Rocky Mountains near Boulder, Colorado, sampled during the spring flood Small stream in Rocky Mountains, near Dillon, Colorado Small stream in volcanic mountains west of Hilo, Hawaii C o a s t a l b l a c k w a t e r lake near Chapel Hill, North C a r o l i n a Eutrophic lake in the Sandhills of N e b r a s k a Small lake in Rocky Mountains, near Boulder, Colorado Small lake in Cascade Mountains, s o u t h west of Mount St. Helens, Washington River in southeastern Georgia originating in Okeefenokee swamp and flowing across northern Florida to the Gulf of Mexico Marsh on northern side of Hawaii, Hawaii Composite of 100 ground water wells in Welton-Mohawk Valley near Yuma, Arizona Yuma canal water after chlorination and sand-filtration Shallow carbonate aquifer supplying water for Miami, Florida

DOC concentrations in these aquatic environments ranged from 0.8 (rag C)L - I in Deer Creek to 32 (mg C)L - I in the Suwannee River.

The percentage of the DOC that was

present as aquatic fulvic acid, as defined by retention on XAD-8 resin at pH 2, ranged from 215 in chlorinated groundwater from the Yuma Canal to 805 in the Suwannee River.

68 Potentiom e t r i c m easurem ents Solutions of H+-saturated aquatic £ulvic acids with dissolved organic carbon (DOC) concentrations ranging from 3 to 20 (mg C)L - I and w i t h 10-3 M KINO 3 as a background e l e c t r o l y t e were made from freeze-dried fulvic acid i m m e d i a t e l y prior to the potentiom e t r i c measurements. analyzer.

DOC concentrations were measured w i t h a Technicon carbon

The pH o£ the aquatic fulvic acid solutions was adjusted to 6.25 + 0.05 by

adding about 4 x 10-4 ~,~ NaOH and bubbling continuously w i t h I% CO2(g) in N2(g). The pH generally decreased to about 6.20 during the subsequent Cu t i t r a t i o n .

Copper t i t r a t i o n s

were performed by incrementally increasing the t o t a l Cu concentration from either 10-7 or [0 -6 M to 10-4 ~! and measuring the corresponding cupric-ion a c t i v i t y .

Cupric-ion

a c t i v i t y was measured with an Orion 801 pH meter, a Radiometer Selectrode F 3000, and an Orion double-junction reference electrode; pH was measured with an Orion 701 pH meter and an Orion pH electrode.

Measurements in freshly prepared solutions of 10-5,

10-6, and [0 -7 M Cu(NO3) 2 and 10-3 M KNO 3 at pl-! 4 were made before each Cu t i t r a t i o n to verify Nernstian response of the cupric ion selective electrode [ 8 ] .

Several blank

titrations also demonstrated r'lernstian response of electrode under the experimental conditions.

It has been shown that fulvic acid is not adsorbed by electrodes made of

graphite, such as the Radiometer Selectrode F3000 used here [ 9 ]

and, therefore, the

response o£ the electrode should not have been altered by the presence o£ dissolved fulvic acid. Additional details of the procedure for the Cu titrations are described by McKnight and Morel [ 10 ]. For some aquatic fulvic acids, the Cu titrations were begun at 10-7 M t o t a l Cu instead of 10-6 M, in order that less abundant but stronger binding sites could be detected.

Cu

titrations of the Suwannee River fulvic acid, begun at both 10-7 and [0 -6 M t o t a l Cu, were analyzed using I=ITEQL (discussed in next paragraph).

Equilibrium constants and

t o t a l concentrations found for these two sets of t i t r a t i o n data were quite similar (Table 2). This result indicates that the analysis is not significantly biased by the starting point of the Cu t i t r a t i o n under these experimental conditions, at a constant concentration of fulvic acid.

However, concentration of aquatic fulvic acid used in the Cu titrations is

important.

At lower fulvic-acid concentrations, the less abundant Cu(ll)-complexing

ligand sites are less likely to be discerned. On the other hand, i t is important to perform the Cu titrations at fulvic-acid concentrations that are not much greater than those of natural waters (Table I), to avoid aggregation or other interactions between fulvic-acid molecules that would not occur in natural waters. Interpretation of p o t e n t i o m e t r i c measurements Data from the Cu titrations were analyzed using FITEQL, a computer program for the determination of chemical-equilibrium constants from experimental data [ I ! ].

The

o p t i m i z a t i o n procedure in FITEQL is based on a linear least-squares f i t and i t e r a t i v e linear approximation of the chemical-equilibrium equations. In the case of a two-ligand model, the appropriate chemical equilibrium equations are"

69

Kt =

[Cu(II)L! ] [Cu 2+]

K2 =

(1)

[L[ free ]

[Cu(II)L 2 ] [Cu 2+]

(2)

[L 2 free ]

LI t o t a l =

[ C u ( I I ) L I ] + [ LI f r e e ]

(3)

L2 t o t a l =

[ Cu(II)L2 ] + [ L2 f r e e ]

(4)

CUtota I =

[Cu 2+]

(5)

+ [Cu(II)LI]

+ [ Cu(II)L 2 ] + [ C u C O 3 ( a q ) ].

Both the c o n d i t i o n a l - f o r m a t i o n constant~ K, and the t o t a l e q u i v a l e n t - l i g a n d c o n c e n t r a t i o n , L, f o r each ligand were t r e a t e d as adjustable p a r a m e t e r s .

These c a l c u l a t e d f o r m a t i o n

constants are conditional~ in t h a t t h e y are only valid a t the pH o f the t i t r a t i o n , 6.201 and a t ionic s t r e n g t h ~, l0 -3 M. In the o p t i m i z a t i o n procedure, the variance b e t w e e n the model

TABLE 2 V e r i f i c a t i o n of e x p e r i m e n t a l and c o m p u t a t i o n a l m e t h o d s by s h o w i n g r e p r o d u c i b i l i t y for t h e S u w a n n e e R i v e r ¢ulvic a c i d , a n d c o m p a r a b i l i t y b e t w e e n i s o l a t e d f u l v i c a c i d a n d w a t e r s a m p l e for t h e S h a w s h e e n R i v e r . (V = v a r i a n c e b e t w e e n m o d e l a n d e x p e r i m e n t a l d a t a ; D O C = d i s s o l v e d o r g a n i c c a r b o n m l e a s u r e d in m i l l i g r a m s c a r b o n p e r l i t e r ; L = e q u i v a l e n t l i g a n d c o n c e n t r a t i o n in M L- ; K = c o n d i t i o n a l f o r m a t i o n c o n s t a n t , pH = 6.25 + 0.05) Suwannee River Range in total Cu

10-7 to 10-4 M

10-6 to 10-4 M

V

5.6

5.3

12.0

11.8

DOC L1

1.5 x 10-5

1.5 x 10-5

log K 1 L2

5.9 3.2 x l0 -6

33 3.6 x l0 -6

log K 2

7.8

7.7 Shawsheen River

FuI~c acid in 10-~M KNO 3

Filtered water sample

Fulvic acid in water

Range in total Cu

10-7 to 10-4 M

2 x 10-7 to 10-4 M

v

6.#

DOC

20

5.4 2.75 (as fulvic acid) 2.7 x l0 -6

2.5 x 10-6

2.75

Ll

1.8 x 10-5

log K l L2

6.0 0.3 x 10-6

6.1

6.0

----

6 x 10-7

log K 2

-------

7,6

L3

7.6 7.3 x 10-7

log K 3

9.7

----

9.7

l x

10-7

70 and the experimental data (V), weighted accordin~ to the estimated error in the experimental data is minimized. The variance reflects the appropriateness of the model used relative to the data set~ if V > > I, the model is inappropriate, and if V << I~ there are too many adjustable parameters in the model. In general, each C u - t i t r a t i o n data set was modelled with the fewest number of ligands that gave an acceptable value for V, between 0. l and I0.

These values of V correspond to

a relative deviation between model and experimental data on the order of 0.3 to 3.0~ [ 11 ].

Each ligand in the model r e p r e s e n t s an a v e r a g e of Cu(ll)-binding sites with similar

Cu(ll)-complexing p r o p e r t i e s .

The e f f e c t of the p H - d e p e n d e n t f o r m a t i o n of aqueous

CuCO3, which a c c o u n t s for about 10S of the t o t a l Cu a f t e r the organic ligands have been t i t r a t e d with Cu, was included in t h e FITEQL calculations~ using t h e m e a s u r e d pH values a t each t i t r a t i o n point. For the case of a complex m a t e r i a l such as fulvic acid~ it should be e m p h a s i z e d t h a t the equilibrium c o n s t a n t s and t o t a l c o n c e n t r a t i o n s found by t h e FITEQL p r o c e d u r e a r e o p e r a t i o n a l p a r a m e t e r s describing a much more c o m p l i c a t e d physical s y s t e m .

As the

n u m b e r of adjustable p a r a m e t e r s in a model increases~ t h e fit of t h e model to t h e d a t a improves.

However, an increased n u m b e r of a d j u s t a b l e p a r a m e t e r s results in i n c r e a s e d

c o v a r i a n c e among the adjustable p a r a m e t e r s , bringing into question t h e uniqueness of t h e values of the adjustable p a r a m e t e r s .

T h e r e f o r e , the e x p e r i m e n t a l d a t a were modelled by

using t h e f e w e s t n u m b e r of a d j u s t a b l e p a r a m e t e r s t h a t gave an a c c e p t a b l e fit.

Even if

tile adjustable p a r a m e t e r s are not an a c c u r a t e description of the s y s t e m on a microscopic scale, t h e values of equilibrium c o n s t a n t s and t o t a l c o n c e n t r a t i o n s still allow r e p r e s e n t a t i o n of the e x p e r i m e n t a l d a t a in t e r m s of a very small n u m b e r of p a r a m e t e r s . RESULTS Shawsheen River a q u a t i c fulvic acid Two samples from the Shawsheen River were t i t r a t e d : a solution of fulvic acid isolated from the Shawsheen River with XAD-8 and a filtered water sample from the Shawsheen River. The data from the t i t r a t i o n of a solution of the isolated fulvic acid with a DOC of 20 (mg C)L - I (Fig. I) were best fit with a three-ligand model w i t h the strength of the Cu complexing sites decreasing several orders of magnitude with increasing ligand concentration (Table 2). In comparison, the Cu t i t r a t i o n of the f i l t e r e d water sample, which had a DOC concentration of 5.5 (rag C)L - I and a dissolved fulvic acid concentration of 2.75 (rag C)L - I , was best fit with a one-ligand model.

The calculated formation constant for

the Cu-complexing sites in the filtered water sample (log K 1 : 6.1) agrees very well w i t h that for the most abundant ligand sites (L l ) in the Shawsheen River fulvic acid (log K I = 6.0). The contribution of Cu-complexing sites to the f i l t e r e d - w a t e r sample from the L l ligand site in the Shawsheen River fulvic acid agrees to within 10g of the t o t a l Cucomplexing sites in the f i l t e r e d - w a t e r sample.

This result supports the conclusion that

the major Cu-complexing substance in the f i l t e r e d - w a t e r sample is aquatic fulvic acidj the result also supports the use of chemical-equilibrium data obtained with isolated aquatic fulvic acids in calculation of Cu(II) speciation in natural waters. The two stronger

71

g-- 7

© ~

8

I

10

6 5 -LOG(Cu T )

4

Fig. I. Copper t i t r a t i o n of aquatic fulvic acid isolated from the Shawsheen River, Massachusetts. The solution had a dissol.~, organic carbon concentration of 20 milligrams carbon per liter) a pH of 6.25) and I0- M KNO 3 as a background electrolyte.

ligand sites (L 2 and L 3) found in the Shawsheen River fulvic acid were not apparent in the Cu t i t r a t i o n of the Shawsheen River sample, because at the Cu concentration (2 x I0 -7 M) in the Shawsheen River, these sites would be occupied or partially occupied. Aquatic fulvic acids from different environments The conditional formation constants and equivalent ligand concentrations obtained from analysis of Cu titrations of other aquatic l u l v i c acids are presented in Table 3. The most abundant Cu-complexing (L l ) site in all of the aquatic fulvic acids tested had a conditional formation constant, log K l , between 5.4 and 6.6 with a mean of 6.0.

The

standard deviation about the mean value of K I , is approximately a factor of two.

The

concentration of L! sites ranges from 4.4 x 10-7 to 1.9 x 10-6 mole sites per m i l l i g r a m carbon of fulvic acid, with a mean of 1.0 + 0.4 x 10-6 M(mg C) - l .

Considering the large

differences in the aquatic environments and source organic m a t e r i a l from which these fulvic acids were derived, even larger variations might have been expected. If we assume that an average aquatic fulvic acid has a t o t a l of 8 meq g

-I

of t o t a l

acidity (carboxylic and phenolic functional groups), and that the L 1 Cu-complexing sites

72

TABLE 3 Conditional formation constants at pH 6.25, and equivalent ligand concentrations of aquatic fulvic acids from different environments calculated from FITEQL (V = variance between model and experimental data; K = conditional formation constant; L = equivalent Cu(II)-binding capacity, M/mg C = moles of Cu(II) binding sites per m i l l i g r a m carbon of aquatic iulvic acid) Source of Sample

V .

log K 1

L1

log K 2

S h a w s h e e n River a

6.4

6.0

O g e e c h e e River a

7.9

6.1

Ohio River a

5.1

6.6

9.0 x 10 -7

L2 (M(m8 C - l )

(M(mg C - l ) 7.6

2.1 x 10 -7

1.0 x 10 -6

7.9

2.2 x 10 -7

6.5 x 10 -7

8.3

1.2 x 10-7

Missouri River a

2.6

5.9

5.6 x 10 -7

7.6

l.q x 10 -7

S o u t h P l a t t e River a

6.7

6.1

7.0 x 10 -7

8.3

1.1 x 10 -7

Bear River a

4.4

6.0

1.1 x 10 -6

7.8

2.6 x 10 -7

Como Creek a

4.3

5.9

1.3 x 10 -6

8.1

3.2 x 10 -7

Deer C r e e k a

4.1

5.9

8.3 x 10 -7

8.3

1.1 x 10 -7

H a w a i i a n River b

0.3

5.6

1.9 x 10 -6

7.2

6.5 x 10 -7

Black Lake a

4.7

6.3

7.4 x 10 -7

. . . .

Island Lake a

4.6

6.4

9.2 x 10 -7

. . . .

B r a i n a r d Lake a

1.1

5.4

1.2 x 10 -6

7.0

3.8 x 10 -7

&lerril Lake a

0.7

5.8

1.3 x 10 -6

7.6

3.1 x 10 -7

S u w a n n e e River a

5.6

5.9

1.2 x 10 -6

7.8

2.7 x 10 -7

H a w a i i a n Marsh b

3.1

6.0

1.9 x 10 -6

8.0

5.7 x 10 -7

Yuma Canal b

6.3

6.0

5.9 x 10 -7

8.5

1.2 x 10 -7

Yuma Canal b

0.7

5.7

4.z~ x 10 -7

7.8

1.0 x 10 -7

Biscayne a q u i l e r a

0.56

5.6

1.0 x 10 -6

7.5

2.9 x 10 -7

MeanC

--

6.0

8.0

2 . 6 + 1 . 6 x 10 - 7

chlorinated

1,0 + 0 . 4 x 1046

~'~copper t i t r a t i o n p e r f o r m e d f r o m 10 -7 to 10 -4 M t o t a l c o p p e r b c o p p e r t i t r a t i o n p e r f o r m e d f r o m 10 -6 to 10 =4 M t o t a l c o p p e r c m e a n v a l u e s for log K 1 and log K T a r e t h e logs of t h e m e a n v a l u e of K; m e a n v a l u e s log K 2 and L 2 do not include Black Lake and Island Lake s a m p l e s .

for

are bidentate salycilic or phthalic acid type sites, then, on the average, L 1 sites represent 16 5 of t o t a l functional groups. There is significant variation in the strength and concentrations of the second most abundant ligand site (L2). In the Cu t i t r a t i o n data for two of the lake fulvic acids there was no evidence of a second ligand site.

The range in conditional formation constant is

greater than an order of magnitude from I07"0 to 108"5.

The range in the concentration

of mole sites per m i l l i g r a m carbon of fulvic acid is 1.0 x 10-7 to 6.5 x 10-7, w i t h a mean of 2.6 _+ 1.6 x 10=7 M(mg C) - I .

On the average, the L 2 sites represent only 5~ of the

73 carboxylic and phenolic functional groups~ assuming a bidentate site.

A t these minimal

concentrations~ other functional groups, perhaps containing nitrogen or sulfur, may be i_nvolved in Cu complexation.

Participation of these other groups could explain the

v a r i a b i l i t y of the conditional formation constant. The data presented here can be compared with data obtained by other researchers studying Cu(II)-fulvic acid complexes in the same pH range (Table 4).

Using an ion

selective electrode technique involving t i t r a t i o n of a Cu solution with an aquatic fulvic acid, Bresnahan and others [ 12 ] report two classes of Cu(ll)-binding sites.

There is no

evidence in our data for their proposed weaker site with a conditional formation constant of 8 x I03~ but there is excellent agreement with their stronger site and the most abundant (L t) site found in our data both in conditional formation constant and in concentration of sites.

Shuman and Cromer [ 13] studied Cu(ll) complexation by an

aquatic fulvic acid usin~ anodic-stripping v o i t a m e t r y (ASV).

Although sorption of iulvic

acid on the mercury drop can significantly interfere w i t h ASV measurements [ 9, t2 ] their data agree with our data.

In these previous studies, the L 2 sites found here would not

have been detected, because the experimental designs did not include small enough ratios of Cu to fulvic acid.

TABLE 4

Comparison of c~emical-equilibrium data for complexation of Cu by aquatic fulvic acids (M(mg C ) - " = moles of Cu-binding sites per m i l l i g r a m carbon as fulvic acid).

Study

Method d

Conditional formation constant, K

pH

Concentratiop (M(mg C ) - ' )

Br-~esnahan et al. a (1978)

ISE

6.0

1.3 x 106

6.1

1.8 x 10-6

S h u m a n and

ASV

7.0

4.7 x 10 5

5.7

1.3 x 10 =6

ISE

6.2

range: 5 4 x 10 to

range5.t~ to

range" 6 2 x lO- to

1

6.6

/4

Cromer (1979) b This study

x

10 6

x

10 -7

rlver m New Hampshire bcoastal blackwater lake in North Carolina c18 different environments dlSE = ion selective electrode~ ASV = anodic stripping v o l t a m e t r y

DISCUSSION The data presented in this report show that aquatic fulvic acids from a wide range of aquatic environments vary only by a factor of 2 in the conditional formation constants and equivalent ligand concentrations describing the behavior of the most abundant Cu(ll)complexing sites near neutral pH.

This result gives us some degree of confidence in our

a b i l i t y to estimate the importance of complexation by aquatic fulvic acids in an aquatic

74 environment without direct measurement or isolation and characterization of the aquatic fulvic acid.

The DOC concentrations in many surface and groundwaters are less than 5

(rag C)L - ! and, because of the l i m i t a t i o n of cupric ion selective electrodes to tota! Cu concentrations greater than 10-7 M, in these waters direct characterization of the Cu(ll)complexing organic ligands by p o t e n t i o m e t r i c t i t r a t i o n , as was done for the Shawsheen River (Table I), is not possible. Also, the t o t a l Cu concentrations in many natural waters are too low for direct measurement of cupric ion a c t i v i t y by p o t e n t i o m e t r i c or other analytical methods. Aquatic fulvic acids account for 30 to 80% of the DOC in most natural waters (Table I). The lesser percentage is typical for groundwaters w i t h low DOC concentrations, and the greater percentage is typical of organic-rich, darkly colored waters.

A typical

percentage of aquatic fulvic acid for surface waters with a DOC concentration ranging from 2 to I0 (rag C)L - I would be 50 %. Therfore, by measuring the DOC concentration, which is a fairly simple measurement, i t should be possible to estimate the concentration of aquatic fulvic acid in a water sample with an accuracy of about 50 %. By combining this estimate with the mean values for the conditional formation constant and binding capacity of the L I and L 2 Cu(ll) binding sites (Table 3), i t also should be possible to estimate the concentration of Cu(ll)-binding sites associated w i t h fulvic acid for a w a t e r sample with a pH ranging from 6 to 7.

This estimate would not be an estimate of the

total Cu(II)-complexing capacity, but could then be used in a chemical equilibrium mode[ that also includes inorganic complexation, precipitation, and adsorption to model the chemical speciation of Cu. For waters with significant concentrations of dissolved AI, Fe, Pb, or other trace metals forming strong complexes with fulvic acid, c o m p e t i t i v e complexation reactions need to be included in a chemical-equilibrium calculation, and the possible effect of slow exchange kinetics needs to be considered.

For some aquatic

environments, i t may be necessary to include complexation by organic materials other than fulvic acid.

Although dissolved proteinaceous material is usually not a major

fraction of the DOC, for example less than 10~ of the DOC in two southwestern lakes [ 1 4 ] , Cu can form complexes with dissolved proteinaceous m a t e r i a l comparable in strength to Cu(II)-fulvic acid complexes studied here [ 14 ] .

In environments with dense

microbial communities, organic metabolites may be i m p o r t a n t . For example, i r o n - l i m i t e d blue-green algal blooms may produce significant concentrations of e x t r a - c e l l u l a r siderophores, Fe transport agents, that also complex Cu [ 15]. The importance of complexation of Cu by aquatic fulvic acids in natural waters w i l l depend primarily on the concentration of Cu relative to the concentration of Cu(ll)binding sites of the fulvic acid. The range of typical Cu concentrations in waters is from less than i ]Jg L - i to 50 IJg L - I , or from less than I0 -8 to 10-6 M. Cu concentrations can be much higher in Cu-polluted environments.

In the t r e a t m e n t of drinking-water

reservoirs to control algal growth, Cu concentrations range from 100 lag L -1 to ! m g L - I , or I0 -6 to 10-5 M. The range in typical DOC concentration in natural waters is from 2 to 7 (rag C)L -! [ i 6 ] .

Using the estimation procedure presented here, this corresponds to a

75 range in the concentration of the most abundant (L I) Cu(II)-binding sites associated with aquatic fulvic acids of from [ x 10-6 to 4 x 10-6 M/L.

The range in the concentration of

the strong (L 2) Cu(H)-bindin 8 sites is 3 x 10-7 to 10-6 M/L.

Comparing these estimates

with the range in Cu concentrations discussed previously, i t is apparent that the stronger (L 2) sites probably are more important in natural waters, and that the most abundant (L I) sites probably are more i m p o r t a n t in waters receiving large Cu inputs, either as a pollutant or as an algicide. The method for estimating the number of Cu(II)-binding sites associated with aquatic fulvic acid~ expressed as moles per liter~ is shown below for the case where 50Y0 of the DOC is assumed to be fulvic acid. Using equation (I)"

0.5 (DOC)(N) = B

(6)

where DOC is the concentration of dissolved organic carbon in (mg C)L -1 and (N) is the moles of Cu(ll)-binding sites per m i l l i g r a m carbon of fulvic acid (I.0 x 10-6, average of the I$ fulvic acid samples studied); calculate (B)~ the moles of Cu(ll)-binding sites per l i t e r that result from fulvic acid. Other estimates for the concentration of aquatic fulvic acid~ such as color, could be used instead of one based on DOC. A sample calculation for the Shawsheen River with a DOC of 5.5 mg C / L follows:

0.5(5.5)(mg C)L - I 1.0 x 10-6(M(mg C) - I ) = 3.0 x I0-6(MIL)

(7)

This estimate for the concentration of Cu(ll) binding sites in Shawsheen River water, 3.0 x 10-6 M/L, compares well with the value determined by direct t i t r a t i o n of a f i l t e r e d water sample, 2.7 x I0 -6 M/L; the estimate for the mean conditional formation constant~ 106"0, also compares well w i t h the value determined by direct t i t r a t i o n , 106"I. In general, the error in the estimate of the concentration of Cu(ll) binding sites associated with aquatic fulvic acid is expected to be between 50 and I00 Y~. The error may be greater than 50Y0 for

atypical waters~ for example, those with excessive

concentrations of other dissolved metals, AI, Fe and Pb~ that can compete w i t h Cu for binding sites. The i m p o r t a n t Cu species in terms of the biological e f f e c t of Cu is the free cupric-ion9 which cannot readily be determined by direct measurement in most natural waters.

The error in the cupric-ion a c t i v i t y calculated using estimated values for the

concentration of binding sites and the conditional formation constant for aquatic fulvic acid is probably no more than a factor of 5 depending on the ratio of Cu to aquatic fulvic acid. The ability to estimate the importance of Cu(ll)-fulvic acid complexes in controlling the chemical speciation of Cu should be useful in evaluating the effect of Cu inputs~ either natural or anthropogenic, on aquatic organisms. A specific example of where an easy estimate of Cu complexation by aquatic fulvic acids would be particularly useful is the control of algal blooms in drinking-water reservoirs by addition of CuSO 4. Currently CuSO 4 dosages are based on past experience and empirical formulas that do not consider the chemical speciation of Cu. An effective CuSO 4 dosage should t i t r a t e the majority of the Cu-complexing sites of the dissolved fulvic acid [ 17] as was the case in the Mill Pond Reservoir CuSO 4 t r e a t m e n t episode discussed previously.

76

CONCLUSION The main conclusion is that Cu(II)-complexing properties of aquatic fulvic acids from different aquatic environments generally are similar.

This similarity allows for the

estimation of the concentration of Cu(II)-binding sites contributed by aquatic ¢ulvic acids in natural waters from a measurement of the DOC concentration. ACKNOV/LEDGEMENT We thank Carol Bowles for perfoming DOC measurements and Ronald Malcolm and George Aiken for providing several of the aquatic fulvic acid samples. This research was partially supported by a National Research Council Post Doctoral Fellowhip awarded to Diane McKnight.

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