Environ. Sci. Techno/. 1995, 29, 1303-1312
Introduction
Partitioning of Cd, Cu, and Zn in Estuaries WINDSOR SUNG Sung & Associates, 27 Battle Green Road, Lexington, Massachusetts 021 73
The variations in Kd (the partition coefficient) of Cd, Cu, and Zn from several water bodies were reviewed. A surface adsorption model involving the ratio of particulate to dissolved metals, particulate iron concentration, total dissolved solids, and pH was developed from data collected from the Savannah River Estuary. The model was also appled to the Medway River Estuary. The empirical model is simple and allows one to calculate the relation between dissolved and total metals or Kd for different environmental conditions from a particular water body. Data from the San Francisco Bay and New YorWNew Jersey Harbor area were also reviewed, and the variation of Kd from these different water bodies is discussed brief Iy.
The behavior of trace metals in estuarine environments is important for an understanding of geochemical processes and has implications for regulatory purposes. The use of membrane filtration to distinguish between a “dissolved” and a particulate phase for trace metals is a common procedure in many studies. It is increasingly being recognized that a vast majority of historical trace metal concentrations in both riverine and marine samples were probably compromised by improper sample collection procedures and analytical techniques. The Federal Water Pollution Control Act or the Clean Water Act (CWA)directed the United States Environmental Protection Agency (EPA) to promulgate ambient water quality criteria (AWQC) for the protection of aquatic ecosystems. The 1972 and 1977 versions of the CWA was concerned primarilywithend of the pipe controls and best available technology. Effluent standards were established for various industry groups. The ability to measure and control metal levels to the parts per million (ppm, mgIkg or mgIL) level was considered adequate for this purpose. The 1987 amendments to the CWA shifted the emphasis to the receiving water bodies and the AWQC levels. It is now necessary to measure and control metal levels to sub parts per billion (ppb,pg/kg or,ug/L)levels. While the technologies for controlling metal levels in effluent to below ppb exist, it is costly. It is also not clear whether this is always necessary. Recent investigations in the NYINJ Harbor (1) utilizing “clean techniques” showed that the AWQC for many metals were not exceeded in various tributaries, contrary to previous investigations. The USGS NASQAN database has also been called into question (2)in terms of potential metal contamination due to sample handling. The EPA recognizes the difficulties inherent in applying national AWQC to site-specific conditions. The 1992 Interim Guidance on Interpretation and Implementation of Aquatic Life Criteria for Metals allowed for the use of dissolved metal concentration as representing the fraction that is bioavailable. Many states have assumed primacy from the EPA for the National Pollutant Discharge Elimination System (NPDES) established by the CWA. Some states have interpreted the AWQC for metals as referring to the dissolved phase, while others have interpreted the metal AWQC as referring to total recoverable. The ability to relate one phase to the other is now necessary. A 1993 EPA memorandum (3) provided guidance for relating dissolved to total recoverable metals. It utilized the concept of a partition coefficient, Kd, and the total suspended solids concentration (TSS). Values of Kd were to be obtained from ref 4 even though ... these I(d values are suspect due to possible quality assurance problems ... the bias in the estimate is likely to be a conservative one”. The water-sediment partition coefficients from ref 4 were determined from STORET data. Previous investigations have reported an apparent relationship between the partition coefficient and total suspended solids concentration (5). Whether this was a “real” particle interaction effect or a consequence of a “colloidal”fraction being included in the dissolved phase has been the subject of academic debate (a. Recent experimental studies on trace metal solid-solution par“
0013-936W95/0929-1303$09.00/0
Q 1995 American
Chemical Society
VOL. 29, NO. 5, 1995 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
1303
TABLE 1
Data Sources Evaluated for This Paper study
rivers
trace metals
San Francisco Bay (1985) SklO (1986, 1988) NY/NJ Harbor (1991)
1 estuarine 16 U.S. and 2 Canadian 3 (and oceanic)
Cd, Cu, Zn Cd, Co, Cu, Pb, Ni, Zn Ag, As, Cd, Cu, Hg, Pb, Ni, Zn
titioning showed that Kd’s for Cd, Cs, and Zn.are independent of particle concentration but vary with salinity (Cd) and perhaps pH (7). A sorption model incorporating these effects is needed. This study originated with the idea of locating highqualitytrace metal data and developing potential relations between dissolved and total metals. Three studies from San Francisco Bay (SFB, 81, Skidaway Institute of Oceanography (SkIO) (21, and NYlNJ Harbor (1)were reviewed. This covered some 20 rivers (includes some estuarine and oceanic environments). The concentrations of both dissolved and total recoverable Cd, Cu, and Zn show that they are generally well below ambient water quality criteria values (except for dissolved and total recoverable Cu in some cases). The data sources that were evaluated and used for this paper are summarized in Table 1. Empirical relations relating the partition coefficient to pH, total dissolved solids YrDS), and particulate iron were developed. Some observations on how these partition coefficients vary in estuaries were offered.
Theory It is assumed that the operationallydefined dissolved-phase C,consists of at least the two phases Cas(truly dissolved) and C, (colloidal). The particulate C, will also be assumed to consist of C, (adsorbed metal) and C, (residual metal). Thus, for the concentration of total recoverable metal, [M,,,] = [Caql+ [CJ + [Csl + [CJ, where [GI = [Caql + [GI and [C,] = [C,] [CJ. The fraction [C]/Mtotis called a, orfd, the fraction dissolved. This is the translator being sought by the EPA. Partition Coefficient. It would appear that a potential translator mechanism already exists in the form of the partition coefficient. In many studies, the amount of particulate metal is reported as grams per gram of suspended solids (C,), and the aqueous concentration C, is expressed as grams per liter (e.g., mg/L). The partition coefficient in this case is defined as
+
[cpl1[cwl= Kd
(1)
where Kd is the partition coefficient in liters per gram. Thus, one could express total recoverable metal (Mt,,) as [M,,,] = [C,l
+ [C,l[TSSl
(2)
where [TSS]is the total suspended solids concentration in grams per liter. If we substituted eq 1 into eq 2, the total recoverable metal is then equal to [Mt,tI
= [c,l
+ {ICwl&[TSSll
(3)
or
1304 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29. NO. 5,1995
Solving for the dissolved metal concentration yields the final expression:
+
Then a, = (1 &[TSS])-l. The product Kd[TSS]is just the ratio of particulate metal over dissolved metal expressed in the same units (i.e., C, in mg/L instead of g/g): it is dimensionless and has been observed to be fairly constant for particular water bodies from the literature. Therefore, one may expect to find a linear relationship between dissolved metal when plotted against total recoverable metal. The slope of such a plot will give a, for a particular water body. This is the basic premise for the 1993 EPA guidance on relating dissolved to total recoverable metals. However, this slope should vary with environmental conditions such as temperature and salinity. It should be specific only to a given water chemistry. The partition coefficient is a measure of the tendency for a chemical to be bound to the surface. The amount of particulate metal also includes the amount of residual metal. Therefore, there is no a priori reason to expect that Kd should behave as a constant. For example, if C, > C, the proportionality between C,and C, will be lost. Equation 1 assumed that the relation between aqueous and sorbed phase is linear. In terms of adsorption isotherms, the assumption is that the surface is not saturated (Langmuir isotherm) or that the constant ( l l n ) in the Freunlich isotherm is close to unity. StudyApproaches. The study of trace metal partitioning onto solid surfaces can be classified into three approaches. The first approach is field based. Natural water samples are collected and filtered, and the fraction of total metal that is dissolved is quantified. The data reviewed in this study fall within this category. The second approach is to study natural samples under laboratoryconditions. For example, river end-member and marine end-member samples were collected and mixed in the laboratory to simulate natural mixing in refs 7, 9, and 10. Environmental parameters such as pH and temperature c a n be controlled and/or varied in a systematic manner. The third approach is to use well-characterized solid surfaces (usually synthetic) and well-defined solution media. This allows for a better understanding of the underlying reaction mechanisms. The iron oxyhydroxide surface (e.g., amorphous ferric hydroxide, goethite, etc.) has been studied extensively, and the modeling of trace metal adsorption onto iron oxyhydroxide surface has been summarized (11). However, application of laboratoryderived constants to real-world situations remains problematic. Obvious difficulties include the operational definition of dissolved versus particulate species as well as the
100000 10000 1 W
s
1000 I00 10
1
0.I
I IO Total Suspended Solids (mgll)
100
FIGURE 1. Relation between Kd and TSS from SklO. Squares are for Cd, triangles are for Cu, and circles are far Zn.
presence of competitive adsorption among species (with all metals, cations, and anions). A chemical equilibrium model for metals in an estuary has been developed recently to include hydrous ferric oxide as a model sorbent phase (12). The model is useful for mechanistic understandingof metal behavior and has great potential. Actual application of the model for permitting issues remains to be developed as it needs the input of much chemical data (the total concentration of all major cations, anions, and the trace metals are needed in principle). The model calculatesthe concentrationlactivity of individual chemical species. Relating these chemical species to water quality criteria and the operationally defined dissolved metal concentration remains problematic. This Study. This study is somewhat between the first and third approach as described above. Only recently published studies or reports with documented quality assurancelquality control programs with particular attention to proper sampling procedures and proper analytical techniques were included for review. The three studies that were ultimately chosen for review utilized similar care for collection, filtration, and analytical techniques. In particular, the collection and analytical methods for SHO samples are representative and previously reported (2,131. The fulldata set obtained from SkIO includes the following information: temperature, pH, TDS, TSS, dissolved organic carbon (DOC),particulate organic carbon (POC),dissolved oxygen (DO), dissolved and particulate metal concentrations for Cd, Co, Cu, Pb, Ni, and Zn, and particulate Al,Fe, and Mn concentrations. A subset of SUO data for the Savannah River Estuary (SRE)was reevaluated, and a sorption model was developed. The model parameters include pH, total dissolved solids
(TDS),and particulate iron concentration (&). The model developed from the SRE was then applied successfully to the Medway River Estuary (MRE) data, also collected by SHO. Potential adsorption surfaces may include coated (by organics or metal oxyhydroxides) or uncoated clays and oxides. Of the metal oxyhydroxides, the most abundant ones are aluminum,iron, and manganese. Acursoryreview of relative abundance, number of adsorption sites per mass of oxide, and the relative strengths of surface binding point to iron oxyhydroxide as the most probable candidate of choice. The model developed was guided by surface adsorption on iron oxyhydroxide. For example, the adsorption of free Cd ion on such a surface may be written as
+
Cd2+ nEFeOOH ==n=FeOOCd'2-"'+
+ nH+
(7)
where EFeOOH is the surface group for adsorption. If this is a proper mass law description for adsorptionldesorption equilibria, then one can write an equilibrium constant
Kads= {~FeOOCd(2-n1+}n{H+}n{Cd2~}-1{~FeOOH}~" (8)
where ( i } stands for the activity of species i (e.g., {H+}); an equilibrium constant, and its numerical value depends on temperature and pressure and is subject to nonideal corrections. Our empirical model assumed that there is some relation between the free metal ion and the "dissolved" metal concentration. For example, the dissolved species of Cd would include the free Cd2+ion and other complexes such as CdCl+, CdOH+, etc. The Cd complexes can be related
Kads is
VOL. 29, NO. 5, 1995 / ENVIRONMENTAL SCIENCE &TECHNOLOGY
1305
'i 0
I-
- -
P m - I
-
-
I
D
-.
+ + + t -
18
20
22 24 26 28 30 Salinity (parts per thousand)
32
FIGURE 2. Variation of & with salinily from Ssn Francisco Bay. Squares are for Cd, triangles are for Cu, and circles are for Zn.
to the free Cd2+ion activity, the equilibrium constant of complex formation, and the free ligand activity:
+ +
+
+
[Cd(aq)l = [CdZ+l [CdCl'] [CdOH'I ... = [CdZ+I(l &dc,[C1-l + &dOHIOH-l + ... (9) therefore, the amount of dissolved Cd ([Cd(aq)l)is roughly proportional to the free Cdz+ ion concentration (the changing of concentrations into activities and vice versa is notvigorousinthisdiscussion). Iftheamount ofparticulate metal is mostly dependent on sorption equilibrium. then one may be able to write an expression that is somewhat analogous to eq 8 as follows:
K = [particulateCdl{H+}"[dissolved Cdl-' x [particulateiron]-' (10) where x is an exponent. The effectof pH on partitioning is implicit from eqs 8 and 10. This expression was also used to describe the adsorption of copper and zinc on amorphous iron oxyhydroxides (9).
Results K,, and TSS from SUO Data. The entire SkIO data consist of 62 samples. Temperature ranged from 3 to 30 "C; pH ranged from 4.7 to 8.45; TDS ranged from 15 to 30140 mg/ L; TSS ranged from 0.2 to 90.8 mg/L; DOC ranged from 0.1 to 48 mg/L. To further test the dependence of & on TSS, a log-log plot of the &'s and TSS was investigated as in Figure 1. The amount of scatter is considerable. Oceanic samples tend to have low TSS and high pH, and they tend to havethehigherKd's. Somewayofseparatingthesalinity effectsfrom the pH effect is necessary. A relation between dissolvedmetals(Pb,Cd, andZn) normalized to TDSversus pH was reported by ref 2. But a plot of Kd versus TDS will also be complicated by changes in pH. A plot of this is illustrated in data from the SFB. 1306 m ENVIRONMENTAL SCIENCE &TECHNOLOGY I VOL. 29. NO. 5,1995
San Francisco Bay. Samples were collected along a longitudinal gradient of dissolved organic carbon in South San Francisco Bay (SFB) on five cruises from March to October 1985 to investigate the spatial distribution of Cd, Cu, and Zn . Twenty measurementswere made of dissolved and particulate Cd, Cu, and Zn. Suspended particulate matter (SPM = TSS) ranged from 0.1 to 20.7 mg/L; DOC rangedfrom2.0 to4.0mg/L;pHrangedfrom7.6to8.2.The amount of iron in suspended sediments was separately determined from samplingperformed in 1986 and ranged from4.55% to 6.29%. In addition, chlorophyll a,particulate organic carbon (POC), and salinity were also measured. Temperature was not reported. Figure 2 (Figure6 of ref 8) reproduces the variation of 16 with salinity for the three metals. Even though the samples were collected from different seasons, the variation of& with salinity seems to be fairly systematic. The Kd of Zn is always greater than thatofCu, whichin turnisgreaterthancd. Thecorrelation of Zn and Cd Kd with salinity is relatively high (9of 0.88 and 0.69, respectively). SavannahRiverESNary. The SREislocated in Georgia. The drainage basin of this river is distributed between the Piedmont Plateau, which largely consists of deeply weathered igneous and metamorphicsediments, and the Coastal Plain, which contains only sedimentary deposits overlain by organic-rich soils. The data from SRE is a subset of the SkIO data and consists of 11samples. Temperatureranged from 22.2 to 29.2 "C; pH ranged from 5.56 to 8.25; TDS ranged from 30.2 to 29270 mg/L; TSS ranged from 4.2 to 9.6 mg/L; DOC ranged from 3.3 to 5.4 mg/L. The trace metal concentrations of Cd, Cu, and Zn and ancillary data are summarized in Table 2. Figure 3 shows the variation of & with salinity.
Correlations between various combinations of parametenfromthis datawere calculatedfollowingthe discussion above (pH, TDS, particulate iron). The best result was
TABLE 2
Summary of Dissolved and Particulate Metal Concentrations and Ancillary Data for Savannah River Estuarf temp PC) pH TDS lmg/LI TSS lmg/LI h.lpMI Cd IpmoVkgI PulpMI Cu lnmollkg) PtuInM) Zn Inmollkg) PalnM) 25.7 22.2 28.4 28.7 27.0 29.2 28.8 28.5 28.2 27.8 28.5
5.56 6.51 6.52 6.50 6.40 7.01 6.90 7.30 7.71 7.95 8.25
30.2 72.5 2090 3750 5910 8410 10120 13300 19840 24620 29270
8.8 4.2 6.6 8.2 9.6 7.7 8.7 7.8 9.1 9.5 5.7
18 1.9 13 15 22 14 16 14 17 8.5 5.5
110 34 85 110 270 53 53 69 41 60 48
46 18 84 100 140 140 140 130 130 100 79
8.3 12 7.8 9.1 8.4 9.2 8.0 6.9 5.8 4.6 2.6
78 8.3 71 21 26 9.9 17 14 12 9.6 7.3
17 3.0 11 14 20 22 16 11 5.4 3.7 4.7
78 9.7 41 59 72 38 52 41 36 36 21
'TDS. total dissolved solids: Cd. dissolved cadmium concentration; PFa,wrticulate iron concentration.
loooo
io
n
100-
I W
m
Y
100
h 0
I . i
v I I
1
-----+, I
0
-
5
I
!
I
~
.+.-,
~
10 15 20 25 30 Salinity (parts per thousand)
1-
I-.
~
35
FIGURE 3. Variation of K, with salinity fmm Savannah River Estuary. Squares are lor Cd. triangles are lor Cu. and circles are lor Zn.
obtained by regressing the following: log([particulate metal] [TDSI[PJ1 x [dissolved metal-') versus pH where [zl stands for concentration of species i (e.g., [particulate Cdl). [TDSI is the total dissolved solids concentrationin milligrams per liter. [PFJis the paniculate iron concentration in micromol. TheTDStermreflectstheeffectsofsorptioncompetition from major cations and anions, complexation of free metal ions by major anions such as chloride, and nonideal corrections. TDS was originally transformed to a measure of ionic strength, and nonideal corrections were applied via the Davies equation (14). The regression did not work as well as using TDS directly. Perhaps this is a reflection of the importance of chloro complexes (as in the case of Cd) in the partitioning. TDS could be directly related to the chloride concentration when TDS is greater than a few thousand micrograms per liter. The relation between dissolved Cd and the free Cd ion was discussed in the development of eq 9.
The ratio of particulate metal concentration over dissolved metal concentration is similar to &, except in this case both concentrations are expressed in the same units, and particulate iron concentration substituted for total suspended solids. Dissolved metal concentration was reported in moles per kilogram, which was assumed to be equal to moles per liter (the maximum error introduced in this assumption is no more than 3% since the density of seawater is about 1.023 g/L). The particulate metal concentrationcan be converted to grams per liter (multiply bygrammolecularweight) anddividedbytheTSS toobtain C, (g/g). Then 16 can be obtained by dividing C, by the dissolved metal concentration (also converted to g/L). The temperature range was small, and temperature correction was not performed. The variation of DOC was small, and the regression was not improved by including DOC. This was somewhat surprising with respect to Cu. The important statistics of the regressions are summarized in Table 3 and shown in Figure 4. It should be noted that the regression scheme worked for Ni and Pb as well. The dissolvedfractiona,can be developedfwrther. Total metal is the sum of dissolved plus paniculate metal. VOL. 29, NO. 5.1995 I ENVIRONMENTAL SCIENCE &TECHNOLOGY
m
1307
TABLE 3
Regression Statistics for Savannah River Estuary metal
best fit slope. m
standard error of m
best lit intercept b
standard ermr of Y
12
cadmium copper zinc
0.8273 0.9623 1.2087
0.1618 0.2013 0.1522
-3.3451 -3.7903 -5.2942
0.4033 0.5016 0.3792
0.744 0.717 0.875
I
L
I !
-I
5.5
6.0
6.5
7.0
7.5
8.0
8.5
PH FIGURE 4. Regression analysis of Savannah River estuary data. S
res are for Cd, triangles are for Cu, and circles are for Zn.
innuencedmarkedlybytheestuarinesamples. Applications oftheseexpressionsto mainlyfreshwaterconditionsremain to be tested. (dissolved metalltotal metal) = The availability of this model allows one to set constant environmental conditions to elucidate importantprocesses. [l (particulate/dissolved)l-' =a, (11) For example, the behavior of a, undergoing estuarine The regression provides the following information: mixing (with concurrent variations in both pH and TDS) can he calculated. This is illustrated in Figure 5 using Cd (particulate metal/dissolved metal) = as an example. TDS was chosen as a measure of mixing 10b+mpHIPFel [TDSI-' between freshwater (pH = 5.56and an assumed alkalinity of 0.167 mequiv/L) and seawater (pH = 8.25and alkalinity therefore =2,30mequiv/L). Equilibriumconstantsforthecarbonate system at 25 "CwereusedforcalculatingpH.The calculated a, = 11 iobfmpH[~,,i [TDSI-~I-' (12) pH for each TDS was used as input to calculate a, via eq 12, assuming a constant amount of particulate iron. This Mternatively,one coulduse this information to calculate was the solid curve in Figure 5. There was a rapid rise in 16: a,with a small amount of mixing (mainly due to the TDS effect). a, remained fairly constant over a wide range of K,,(llg) = 10b~+mpH~PFel~TDSl~l~TSSl~l (13) salinity and pH conditions. However, the pH effect becomes important as it increases beyond 7,and a, where TSS is in grams per liter. Values of b and m from eventually decreases again. Table 3 are based on TDS reported (in mg/L) and 9, (in The calculated pH frommixing tended to undercalculate PM). pH by about 0.6 unit, so that the modeled a, was higher The relative simplicity of eqs 12 or 13 was somewhat than the observed values (plotted as open squares). The surprising. Additional refinements to improve the model amount of particulate iron was also varying. The calculated are possible (e.g., temperature, DOC). Initial attempts to a,utilizedobservedpH,TDS,andtheamountofparticulate improve the correlation hy incorporating surface site iron, utilizing the regression constants (plotted as open limitations did not provide better results. The amount of circles). The fit is by no means perfect, hut the general sufacecoveragebytracemetalswasfairlylow(onthe order trend is correct. This is in agreementwith many observed of 2-10 lmollg of suspended solids). While the exprestrace metal concentration profiles along salinity gradients. sions take TDS into explicit consideration. the results were
Dividing both sides of eq 6 hy dissolved metals and taking the reciprocal gives the expression:
+
+
(308 m ENVIRONMENTAL SCIENCE &TECHNOLOGY I VOL. 29, NO. 5.1995
5.5
6.0
7.0
6.5
7.5
8.0
8.5
PH FIGURE 5. Regression analysis of Medway River Estualy data. Squares are lor Cd, triangles are lor Cu. and circles are lor Zn. TABLE 4
Summary of Dissolved and Particulate Metal Concentrations and Ancillary Data for Medway River Estuarf temp PCI
pH
TDS ImgILI
TSS (mg/Ll
&bM)
Cd Ipmolikg)
8.1 8.1 7.5 7.3 7.6 7.0 7.8
5.65 5.71 6.54 7.40 6.90 7.39 7.54
15.1 33.1 900 2250 2330 4840 7890
1.3 1.o 4.1 4.0 4.1 4.0 4.1
0.7 0.6 0.9 0.7 0.5 3.8 0.3
270 120 99 96 73 1500 99
PM IpM)
Cu Inmolikg)
RulnM)
Zn (nmolikgl
R.(nMI
5.3 7.3 4.5 5.0 9.4 6.8
7.0 2.9 3.4 0.6 1.4 4.3
25 15 0.5 0.5 7.9 1.7 n4
17 15 16 3.3 6.1 27
120 19 48 11 11 200
'TDS. total dissolved solids; Cd. dissolved cadmium concentration; P F ~paniculate , iron concentration.
The behavior of trace metals from the SRE have been previouslyreported for uranium (13,for copper (1@,and for plutonium and lead-210 (17). This is also in agreement with the modeled results (free Cd ion concentration) from ref 12. Alternatively, one could use eq 13 to calculate the variation of Kd for other modeling or permitting applications. Medway River EsNary. The originalhope was to apply the SRE model to the entire SkIO data. It was not as successful. But another subset oftheSkIO data, the Medway RiverEstuary(MRE1inNovaScotia, Canada, offeredauseful comparison. It consisted of 12 samples. Temperature ranged from 3 to 8 "C; pH ranged from 5.71 to 8.03; TDS ranged from 15.1 to 30140 mg/L; TSS ranged from 1to 4.1 mg/L. The trace metal concentrations of Cd, Cu, and Zn and ancillary data are summarized in Table 4. Similar regressionswere performed, and the results are presented in Table 5 and Figure 6. This shows that the relationships as described by eqs 12 and 13 can he developed for individual water bodies. NY/NJ Harbor. EPA region I1 and the States of New York and New Jerseyhave declared that the waters of New
TABLE 5
Regression Statistics for Medway River Estuary metal
m
standard error of m
b
standard error of Y
r2
cadmium copper zinc
0.9991 1.0131 1.4937
0.169 0.1646 0.2479
-4.5320 -4.2757 -6.6412
0.4797 0.4664 0.7025
0.776 0.791 0.783
YorklNew Jersey Harhor (NY/NJ Harbor) are impaired under the provisionsof Section 304 (I) of the CWA. In light of all the concerns over metal contamination, an ambient evaluationsurveywas carriedout in the NY/NJ Harborusing clean techniques. The study encompassed three rivers as well as estuarine and oceanic samples. A field survey was conducted i n J a n u q 1991to collect ambient water samples at 37 stations in the NYINJ Harbor and effluent samples from 21 municipal sewage treatment plants (STP). All samples were analyzed for the trace metals Ag, AS, Cd, Cu, Hg, Ni, Pb, andZn; total suspended solids (TSS);particulate carbon (PC);and dissolved organic carbon (DOC). Metals were determined in four phases: total recoverable, acidVOL. 29,
NO. 5.1995 / ENVIRONMENTAL SCIENCE & TECHNOLOGY.
1309
0.8 c
0.6
Q
0.4 0.2
m
-/ 0
5
10 15 20 25 30 Salinity (parts per thousand)
35
FIGURE 6. Behavior of Cd a, in the SRE. The line assumes both pH and TOS are determined by the mixing of freshwater and seawater and a constant R. 113.2 mMI and calculates a, using modeled pH and regression constants. Squares are the observed a,,and circles are calculated a, using observed pH. TDS. Re.and regression constants.
soluble, dissolved, and particulate. Final data report was dated September 1991( I ) . Afield surveywasalso conducted inMay 1991to collect amhientwater samples at sixstations in the NY/NJ Harbor over a fidal cycle and at three NJ tributaries. Another field surveywas conductedinOctoher 1991tocollect low-flowambientwatersamplesat18surface and five bottom water stations in the NY/NJ Harbor. Data for Cd, Cu, and Zn from the January 1991 survey only were reviewed. There are 42 measurements for each parameter (Le., 42 dissolved Cu, 42 particulate Cu, etc.). TSS ranged from 0.61 to 44.4 mg/L; DOC ranged from 1.57 to 5.15 mg/L; and salinity ranged from 0 to 33 parts per thousand. Unfortunately, pH was not measured, and temperature data were difficult to emact from the report for application to our model. There were indications that some contamination occurred for a small number of samples. Figure 7 shows the variation of 6of Cd versus salinity. While there can he a factor 4 variation of & at a given salinity, the variations are more systematic when individual water bodies (e.g., Long Island Sound1 are evaluated. The values and variations of fi for this water body are similar to those of the San Francisco Bay.
Discussion The data reviewed here showedthat amhient levels oftrace metals are generally well below AWQC values, except for copper in some cases. SFB and the NY/NJ Harbors are comparativelymoreimpactedhymetalsthantheSklOwater bodies. Care should be exercised when comparing these studies. The SFB studyis essentiallyamarine environment withlimited spatialvariahility. The SkIO covered avariety of freshwaterand estuarine environmentsalong the eastern North American coast. The NY/NJ Harbor study covered freshwater andmarine environmentswithmoderatespatial coverage,and the data reviewed werecollected in thewinter. The dependence of surface partitioning on pH and TDS (or salinitv) has been demonstrated. To minimize these 1310 m ENVIRONMENTAL SCIENCE & TECHNOLOGY i
VOL. 29, NO. 5.1995
effects,it was decided to compare the I(dls under marinelike conditions (pH of about 8 and salinity about 30-32) as summarizedin Table 6. While there are still substantial variations in the values, some generalizations can he made. SomeofthevariationsinKdcanbeexplainedhydifferences in iron content. Therefore the units of Kd were modified from liters per gram of suspended solids to liters per mole of particulate iron (one needs to know the moles of iron per gram of suspended solids, or percent iron will do). Experimental 16‘s determined from the Humher Estuary (7)and Puget Sound (10)are also included for comparison. Comparison of the SRE and MRE data suggests a temperature effect since the former is close to 25 “C and the later is close to 5 “C, hut it would entail a negative standard enthalphy change (especiallywiththe converted fi in liter per mole). A more compelling trend (but harder to quantify] can he attributed to level of “pollution”. The SFB andNY/NJHarborhavehighertotalmetalloads(more competition for adsorption sites) than SRE or MRE, and they have corresponding lower Kdk Alternatively, there may be real differences in the surface characteristics of these particulates from various water bodies. The variation of Cu Kd is actually higher expressed in liters per mole of particular iron than expressed in liters per gram of suspended material. Both refs 8 and 10 discussed the effects of organics on the binding of copper toparticulates. Paulson (10)investigatedtheeffectsofDOC on copper partitioning experimentally. He showed that Cu Kdincreased by a factor of 2 when DOC was removed. The work of ref 8 also showed some dependence of Cu Kd with POC.
Conclusion The present EPA guidance does not always provide for conservative estimates for the translator. It relies on the use of potentially compromised data. The application of the EPAguidance is also problematicfor estuarine systems.
25
n
m
’s
20 I
I
15
10
5
A
5
10
15
20
25
30
Salinity (parts per thousand) FIGURE 7. Variation of Cd Kd with salinity from NVNJ Harbor. Squares are from the Arthur Kill, triangles are from the Hudson, and circles are from the Long Island Sound. TABLE 6
Summaty of Marine Kd location
Cd Kd (Ugl
San Francisco Bay NYINJ Harbor Medway River Estuary Savannah River Estuary experimental
2.5 14 65 100 0.75a
log Cd & IUmoll
Cu & 1Ugl
log Cu & (Llmoll
4.4
14 51 129 140 32t065b
4.2 NA 5.6 4.9 NA
NAC 5.3 4.8 3.6
Zn & IUgI
log Zn & Illmoll
19 31 5100 225 10.W
4.3 NA 7.2 5.1 4.1
From ref 7, Hurnber Estuary, U.K.. relatively high suspended solids. a F ~ a m ref 10, Puget Sound. WA. INA, not available
Asurface adsorption model for Cd, Cu, andZninvolving the ratio of particulate to dissolved metal was developed from the SkIO data with the following parameters: particulate iron, total dissolved solids (TDS), and pH. This model was first derived from the Savannah River Estuary @RE) data produced by SkIO with relatively good results (correlation coefficients of 0.72-0.88). The same model was then applied successfully to the Medway River Estuary, another subset of the SkIO data, with similar results (correlationcoefficients of0.78-0.79). The empiricalmodel allowsone toquantifytheeffectsofTDSandpHonsurface partitioning (temperature effects can be accommodated) to calculate & or G. This can be useful in modeling purposes such as the mixing of river end-members with marine end-members. The values of & from different water bodies were compared. The use of particulate iron as the adsorbing sulface for Cd and Zn is promising and warrants further investigation (e.g., incorporating temperature and solution complexation effects, site limitations as well as surface characteristics). The relation between Cu Kd and DOC/ POC remains to be developed.
Acknowledgments This work was supported by the U.S. Environmental Prctection Agency, Office of Water (Contract 68-CO-0093).
While this research was supported by this Agency, it has not been subjected to Agency review, and no endorsement of this work by the Agency should be inferred. The author thanks Keith Sappington, Charlie Delos, and Dr. Herbert Windom for making this paper possible. SkIO data used inthis paperwasproducedunderNSFGrantOCE-8600287.
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