Hydrobiologia 235/236 : 533-544, 1992 .B. T. Hart & P. G . Sly (eds), Sediment/Water Interactions .© 1992 Kluwer Academic Publishers . Printed in Belgium .

Arsenic transport between water and sediments

Jack Cornett, Lorna Chant & Bert RistoEnvironmental Research Branch, Chalk River Laboratories, Chalk River, Ontario KOJ IJO

Key words: arsenic, sediments, distribution coefficient

Abstract

Arsenic discharged into the Moira River has accumulated in the sediments of Moira Lake during thepast century . The chronology of arsenic concentrations in the sediments, established using Pb-210 dating,has a subsurface concentration maximum (> 1000 tg g - ') that reflects higher inputs to the lake 15 to45 years ago . The distribution coefficient (K d ) of arsenic in the surficial sediments was low (4000-6000 L kg - ') and decreased below the sediment water interface . Higher concentrations of exchangeableAs also were extracted deeper in the sediments . As a result, arsenic is mobile in the sediment columnand the flux of arsenic via diffusion and particle resuspension from the sediments into the water is greaterthan current external loading from the Moira River . Less than 20%s of the external input of arsenic isburied in the lake sediments . Using these flux measurements and a one dimensional model of arsenictransport in the sediment column, we constructed the history of arsenic exchange between water andsediments throughout the past century . The simulations predict that arsenic input into the water fromthe sediments has been > 20% of external loading for the past 25 years and will continue to be importantin the future as diffusion and resuspension regenerate arsenic from the mixed layer of the sediments intothe overlying water .

533

Introduction

Many trace contaminants discharged into fresh-water are transported to locations of bottom sedi-ment accumulation (e.g . Santschi et al., 1986 ;Cornett & Ophel, 1986 ; Cornett & Chant, 1988) .Once deposited in the surficial sediments, thecontaminant may be recycled back into the waterby particle resuspension or desorption and diffu-sion, or buried deeper in the sediment column bysubsequent sediment inputs (Thomann & DiToro, 1983; Diamond et al., 1990). The relativeimportance of these internal fluxes, external load-ing and hydrologic flushing determine the fate ofthe contaminant in the system, and the rate thata contaminated system will recover .

In this paper we examine the distribution, fluxesand fate of one trace contaminant, arsenic, inMoira Lake, a small hardwater lake that has re-ceived discharges from tailings and milling oper-ations during the past century (Mudroch & Ca-pobianco, 1980; Evans et al., 1986 ; Cornett et al.,1989). We have used these measurements to de-termine the historical chronology of arsenic in-puts to the sediments, to determine the mobilityof arsenic within the sediments, to construct amass balance for arsenic in the lake and to testthe hypothesis that the internal loading of arsenicfrom the lake sediments into the water column is,currently, greater than the external loading .

534

Experimental details

Moira Lake is a shallow (mean depth 4 .4 m),hardwater (pH -8.0, total dissolved solids- 200 ppm), dimictic lake (area 827 ha) locatedabout 100 km north of Lake Ontario (see Evanset al., 1986). The lake was formed by a wideningof the Moira River, which flushes the lake at amean rate of 2 .9 times per annum (Water Surveyof Canada, 1988) .

The complex history of ore milling operationsin the Moira Lake Basin is only known qualita-tively (Bowles, 1982) . There are significant quan-tities of wastes located in tailings sites along theMoira River. Although groundwater leachate andrunoff from the tailings site are treated by a waterpurification plant, As and other trace inorganiccontaminants still leach into the Moira River (Di-amond, 1990). Arsenic is the only metal moni-tored in the Moira River . Records suggest thatthe amount of As entering the lake has decreasedsince refining operations ceased in 1961 (OntarioMinistry of the Environment, unpublished data) .The surficial concentrations of many trace metalsin Moira River sediments and in the lake sedi-ments are higher than background levels and thereare significant enrichments of As, Ni and Co(Mudroch & Capobianco, 1980 ; Cornett et al.,1989) .

Inflow, outlet, lake water samples and cores oflake bottom sediment were collected while thelake was isothermal during fall turnover . Thesampling locations reported by Evans et al. (1986)were used in this study . Cores were collected witha K-B gravity corer, using 7 cm inner diametertubes, at sites where soft, organic rich sedimentsaccumulated (LOI 30-45%) . The cores used tomeasure redox sensitive species were sectioned in1 cm or 2 cm sections under a positive nitrogenatmosphere to maintain the in situ redox condi-tions . As an additional precaution against the in-trusion of oxygen, the outer ring of core material(0 .5 cm) was separated from the inner ring ofeach section and the outer ring was not used forredox sensitive analyses . During subsequent sam-ple processing for redox sensitive parameters, anitrogen atmosphere was always maintained over

the samples (see Cornett et al., 1989). Subsam-ples of sediment were extracted using the sequen-tial extraction procedure of Tessier et al. (1979)using the modifications described by Cornett et al.(1989) to prevent the intrusion of oxygen . Theporewaters were separated from the matrix bylow speed centrifugation under a nitrogen atmo-sphere in a glove box. Then the supernatant wasdecanted off and filtered through prewashed0.4 µm polycarbonate filters . Lake water samplesalso were filtered through the same type of filtersto define dissolved and particulate arsenic con-centrations .

Arsenic was analyzed by atomic absorptionspectroscopy using borohydride generation (Pea-cock & Singh, 1981) . The accuracy and precisionof our arsenic analytical techniques were evalu-ated by analyzing internationally accepted certi-fied reference standards. We analyzed IAEA-W-4, a simulated freshwater standard and IAEA-SL-1, a freshwater lake sediment sample . Themeans of triplicate analyses of these samplesagreed well with the certified values . None of thedeviations from the certified values were statisti-cally significant . The coefficient of variation fortriplicate analyses ranged from 4% for solublesamples to 17% for sediment samples . As notedin other studies, the variability in analyzing sedi-ment samples was higher than that for water sam-ples .

For Pb-210 analyses, five cores were selectedto provide coverage of the range of zones of sedi-ment accumulation . Core sections were dried toconstant mass, crushed and homogenized using ashatter box so that the powder passed through a100 mesh screen. The concentration of Pb-210was determined assuming secular equilibrium be-tween Pb-210 and its daughter Po-210 . The ac-tivity of Po-210 was measured using alpha spec-trometry. The extraction and plating technique ofEakins and Morrison (1977) was modified slightly(Cornett et al., 1984). To obtain acceptable re-coveries of the Po-209 yield tracer (mean recov-ery 75%), the Po was volatilized from the sedi-ments at 650 to 700 °C and/or the sample wasdigested using a microwave enhanced acid disso-lution. Then the residue was leached in concen-

trated nitric acid . Following removal of the nitricacid by evaporation, Po-210 was spontaneouslyelectroplated on silver discs in a 1 .5 N solution ofHCl over a period of 16 to 24 hours . The discswere counted using surface barrier detectors, andthe counts accumulated in a multichannel ana-lyzer .

Three procedures were used to determine theaccuracy and precision of the Pb-210 analyses .First, we used a radiochemical yield tracer (Po-209) traceable to NB S SRM 4327, and confirmedthe yield tracer activity against Pb-210/Po-210solutions from Amersham Nuclear, and otherlaboratories . Second, we measured the activity ofCANMET, Energy Mines and Resources SRMDL-lA and our results agree with the expectedvalue. Finally, blanks analyzed by our proceduresshow no detectable activity above counter back-ground. The background of the counting systemwas monitored at approximately bi-weekly inter-vals and was found to be < 1 % in all but thelowest activity samples .

Results and discussion

Pb-210 dating and sediment accumulation

The concentrations of Pb-210 plotted in Fig . 1followed classic log-linear depth profiles (Rob-bins, 1978). Activities in the surficial sediments(0.5 to 0.9 Bq g -1 ) were similar to the valuesmeasured in other small lakes with organic richsediments (e.g . Evans & Rigler, 1980 ; Cornettet al ., 1984). In the top 3-8 cm of the cores, Pb-210 concentrations changed very little with depth,indicative of a mixed layer within the sediments(Robbins, 1978; Robbins et al., 1977). In somecores, the surficial Pb-210 concentration wasslightly lower than the concentration measured inthe second depth slice . However, in all but onecase (Core 10), these measurements are withinthe uncertainty in the analyses (average coeffi-cient of variation 7 % ) . Below the mixed layer, thePb-210 concentrations decline continuously withdepth and suggest that the accumulation of Pb-210 and sediment has been continuous . This is

1 .5

0.5

#1 #10

5 3 5

Fig . 1 . Measured () and simulated (

) concentrations ofPb-210 in 5 sediment cores .

further supported by measurements of stable Pbin the cores (Evans et al., 1986) and the analysisof the bulk composition of sediments which isquite uniform with depth in all cores except incore 10 (Cornett et al., 1989). The fluctuations inthe Pb-210 exhibit a subsurface maximum andthen rapidly decrease (Fig . 1). The physical char-acteristics and geochemistry of this core alsochange as the sediment type changes from gyttjato coarse sands below the depth of 10-12 cm(Cornett et al., 1989). This anomalous Pb-210profile may reflect a recent increase in sedimentaccumulation at this near shore location .

We interpreted the Pb-210 profiles using theCIC mixing model (Model 3) of Robbins (1978) .This model uses the advection-diffusion equationto describe the depth (Z) distribution of Pb-210

53 6

under the assumptions that the depth distributionis at steady state and is described by :

8CS/dt = 0(Eb0CS/oZ)0Z - waC s/8Z - 2CS . ( 1)

Using model 3, Eqn. 1 can be solved and thechange in CS can be described by a set of sixparameters that are constant with time and onlythe mixing coefficient changes with depth . Theparameters are : the rate of sediment accumula-tion (w, cm yr -1 ), the activity of Pb-210 in set-tling particles (Cs , Bq g- 1 ), the background ac-tivity of Pb-210 supported by Ra-226 (C 0 ,Bq g -1 ), the depth of the surficial mixed layer(Zmix , cm), the mixing coefficient in the mixedlayer (Eb, cm2 yr- 1 ) and the radioactive decayconstant (A, yr -1 ) . Since the porosity in the coresis very high (95-98% in surficial sections) anddecreased to only - 90 % in the top 30 cm of thecores (except in core 10 below 12 cm), changes inporosity have a small impact on the calculation ofthe core chronology (Robbins, 1978) . Therefore,we have ignored this variation with depth .

The simulated Pb-210 profiles fit the measureddepth profiles and using the square of the corre-lation coefficient as a criteria, explain 60 to 95of the variability in the measured concentrations(Fig. 1). The parameters calculated by fitting themodel to the Pb-210 profiles are summarized inTable 1 . The poor fit to core 10 probably reflectsrecent changes in the sediment accumulation rateat this location (Cornett et al ., 1989) and the ap-plication of the CRS model might be more ap-propriate since this model allows the value of wto vary with depth (Appleby & Oldfield, 1979) .Rates of sediment accumulation range from 0 .15

Table 1 . Parameters used to fit fthe Pb-210 profiles and theresidence time of particles in the mixed zone (Y)

to 0.32 cm yr -1 . Corrected for compaction, thesediment accumulation rates are 80 to300 g m -2 yr -1, and are similar to those mea-sured in other mesotrophic/oligotrophic lakes(e.g . Evans & Rigler, 1980 ; Robbins, 1978). Therates of bulk sediment accumulation correlate wellwith the rates of arsenic accumulation in the sed-iments (R = 0.9, N= 6). This correlation betweenbulk sediment accumulation rate and elementalaccumulation appears to be valid in a diversity oflakes for many elements (Evans et al., 1986) .

We interpret the shape of the Pb-210 profilesnear the interface as evidence that the sedimentsare mixed (Fig . 1) with a mixed or bioturbationlayer 3 to 8 cm thick (Table 1). The ratios of therates of mixing to sediment accumulation aregreater than 40 so that the concentration gradientof Pb-210 near the interface cannot be resolved(Robbins, 1978) and only a lower limit to the rateof mixing can be determined (Eb > 20 cm2 yr -1 ) .If the mixed layer was completely and instanta-neously mixed, then the residence time of parti-cles in this layer ranges from 9 to 33 years in the5 cores (Table 1) . The age of each core sectionwas calculated using the sediment accumulationrates presented above, correcting for the thick-ness of the mixed layer by assuming mixing in thislayer is instantaneous .

Distribution of arsenic

The vertical distribution of As below the mud-water interface and the areal distribution of theelement in the sediments were examined usingsediment cores collected during 1983 and 1985 .Evans et al. (1986) reported Ni concentrations in15 cores of Moria Lake sediments . In this study,we measured the As concentration-depth profilein 6 of those cores .

Arsenic concentrations measured in the MoiraLake sediments are very high (> 500 µg g -1 ,Fig. 2a). These arsenic concentrations are muchhigher than those reported in most other systems(e.g . Aggett & O'Brien, 1985 ; Hakanson & Jan-sson, 1983 ; Nriagu, 1983) . The vertical distribu-tion of As exhibits large changes in concentrationthroughout the core profile . Maximum concen-

Core W(cm yr - 1 )

Eb(em2 yr - I)

Zm; x(cm)

(Y)(yr)

1 0 .20 >20 5 2510 0 .15 >20 8 -11 0.15 >20 5 3313 0.45 >20 4 915 0.32 >20 3 9

2000

1500

Ea.1000

Q

500

0

Fig. 2 . Arsenic concentrations in the sediments plotted against the depth of the core section (a) (core # 2 A, 6 •, 8 -, 11 *, 13c, 15 A) and the age of the section (b) core # 11 *, 13 a, 15 Fj) .

trations, located between 10 and 20 cm below themud-water interface, often exceeded 1000 µg g -1 .Peak arsenic concentrations are located at differ-ent depths and the shape of the depth profilesdiffer among the cores (Fig . 2a). The maximumconcentrations were usually 5 to 10 times greaterthan values found near the surface or maximumdepth of the core. We believe that the changes inconcentration of As in the lake sediment coresreflect different accumulation rates of As in thedifferent cores during the past 150 years . Thishypothesis was tested by dating several cores .

The depth-age chronology and the rates ofsediment and arsenic accumulation in three coreswere determined using the Pb-210 profiles pre-sented earlier . The differences in As depth pro-files can be explained by the different rates of bulksediment accumulation and mixing in the surficialsediments . The relationship between arsenic con-centration and the age of the sediment sections is

537

very similar in the cores after these correctionsare introduced (Fig . 2b). In each core, As con-centrations increased after ,:,1850, were highestbetween 1945 and 1975, and have decreased re-cently. This history inferred from the sedimentsagrees qualitatively with the complex history ofmilling and tailings management in the MoiraRiver Basin (Mudroch & Capobianco, 1980 ;Bowels, 1982) . Milling activity in the basin in-creased after 1860 and As discharge has declinedduring recent years as leachate effluents have beentreated to remove As (Environment Ontario, un-published data) . However, the historical inputs ofAs to the lake are now known quantitatively .

The porewater concentration of As that passedthrough a 0 .40 µm filter were determined in coresfrom two sites (sites 1 and 10 in Fig . 1) . Arsenicconcentrations in the porewater mimicked thedistribution of the element in the matrix . A sub-surface peak in concentration of ,: 1 mg I -1 was

538

significantly higher than concentrations measurednear the mud-water interface or the maximumdepth of the core (Fig . 3a) .

The total As concentration in the lake watersamples was 47 ± 3 µg I -1 and only 4 .0 % of theAs was retained by filtration through a 0 .4 µmfilter, giving a dissolved As concentration of45.1 ± 2 .8 mg 1-1. The lake was isothermal at thetime of sampling (Cornett et al., 1989) so thesesamples are representative of the entire water col-umn. Since the concentration measured in theporewater, As will be transported along this con-centration gradient from the sediments to thewater .

The partitioning of arsenic between the solidand dissolved phases was calculated using thedistribution coefficient (Kd) . Kd was defined asthe concentration of As on the solid phase(mg kg-1) divided by the As concentration in the

1 .4

1 .2

1

NQ0 .6

0 .4

0.2

00 5 10 15

20Depth (cm)

25 30

dissolved phase (mg 1- 1) . Kd values were highestfor particles in the water column and lower in thebottom sediments (Fig . 3b). This observation isconsistent with empirical and theoretical argu-ments which predict that Kd values are higher inthe water column than in the bottom sedimentsbecause the particle concentration is about 104times higher in the sediments than in the water(O'Connor & Connolly, 1979 ; Di Toro et al.,1986; Vezina & Cornett, 1990). Within the sedi-ment column, the Kd values decreased below thesediment-water interface . The decline in Kd val-ues correlates with the decline in Eh within thesediments (Cornett et al., 1989) . All of these mea-surements of As partitioning are consistent withthe behaviour of a redox sensitive compound (Ag-gett & O'Brien, 1985) .

To test further the mobility of As within thesediments, sections of core # 1 were analyzed

6000

5000

4000

mYJ 3000

Y

2000

1000

0 0 5 10

15

20Depth (cm)

25

Fig. 3 . Arsenic concentrations (a) and the Kd of arsenic (b) in the sediment porewaters (core # 1 *, core # 10 o) .

30

NaJ

0I0

using selected extractions of the wet sedimentsunder a nitrogen atmosphere. The amount of Asextracted using a 1 M MgC1 2 wash varied from1-3 % in the top of the core to 5 to 12 % below20 cm (Fig. 4). The increase in the concentrationof easily exchangeable As deeper in the core cor-relates with the decline in the distribution coeffi-cient of As below the sediment interface . To es-timate the amount of arsenic bound tooxyhydroxides, the sediments were extracted with0.04 M NH2OH-HCl (in 25% v/v HOAc) for 4hours (Tessier et al., 1979). Sixty to ninety per-cent of the total As in the sections was extractedby this technique (Fig . 4) . The fraction of the Asextracted decreased with depth from 80 to 90in the top 5 cm to 60-70 % at depths below 20 cm .These observations are consistent with the anal-yses by Aggett and O'Brien (1985) and Aggett

100

80

60

40

20

010

15Depth (cm)

Fig. 4 . Percentage of total arsenic in MgCl2 (*) and NH 2OH-HCL (o) extracts of core # 1 .

0 5 20 25 30

5 39

and Robert (1986) . They argued that the arseniccycle in freshwater was controlled by coprecipi-tation of As with hydrous oxides in the watercolumn and the dissolution of this species in thereducing sediments .

Fluxes of arsenic

The fluxes of arsenic through the lake weredetermined from the rates of As input throughthe inflow, outflow in hydrologic discharge, andburial in the sediments (Table 3) . In 1985, thenet difference between the mass of arsenic inthe external load and the outflow was about160 mg m -2 yr -1 . Assuming that the volatiliza-tion of arsenic was negligible, the difference be-tween the external load of arsenic entering thelake and As leaving the lake provides an estimateof the arsenic retained in the lake sediments . Ex-pressed as a percentage of the inflow, the reten-tion of arsenic was about 30% . This is similar tothat of other elements in systems with short hy-draulic residence times (Cornett & Chant, 1988 ;Prairie & Cornett, unpublished data) . The 30%retention of arsenic calculated from the inflowand outflow is 10 to 20% greater than the burialof As estimated from the product of the dry massaccumulation rate multiplied by the concentra-tion of As in the surficial sediments (18% atSite A, 10% at Site B, see Table 3) . This differ-ence may be a result of: (a) the uncertainty in themass balance calculations since the results of afew cores and water samples were generalized tothe entire lake area, (b) other losses (e.g . volatil-ization) that were not considered in this analysis,or (c) a bias introduced when the internal loadingof arsenic was omitted from the analyses .

To evaluate the internal loading of As from thesediments, we calculated the rates of resuspen-sion and diffusion . The fluxes of particles andarsenic between water and the sediments weredetermined from measurements of particle con-centrations, sediment trap catch (from Diamond,1990) and sediment accumulation rates (Table 2) .Particle concentrations in the water column arelow (2 to 26 mg 1 -1 ) and are similar to those

540

Table 2 . Moira Lake particle dynamics and fluxes .

1 . Calculated as CP . z .2. From Diamond (1990) .3 . From Pb-210 dating .

measured in other shallow mesotrophic lakes (e.g .Cornett et al., 1984). The mean residence time ofthe particles in the water column, calculated bydividing the particle mass by the sediment trapcatch, was 8 .5 days. The mean catch of particlesin sediment traps was 4 to 5 times greater than therate of sediment accumulation determined fromPb-210 dating. We interpret the difference be-tween the trap catch and the accumulation rate ofsediment to result from the decomposition of or-ganic matter and from the resuspension and fo-cusing of the surficial sediment floc into zones ofsediment accumulation. Only about 50% of the>400% difference between the two measure-ments can be attributed to decomposition (Cor-nett & Rigler, 1987) . Resuspension rates of 200 to400 gm-2 yr - 1 are needed to account for theremainder. Similar rates have also been deter-mined in other shallow lakes (e .g . Robbins et al .,1990; Vezina & Cornett, 1990). The flux of ar-senic on resuspended particles was determinedby multiplying the concentration of As in the surf-icial sediments (Fig. 2a) by the flux of resus-pended particles (Table 3). The ratio of arsenic

Table 3 . Arsenic fluxes in Moira lake (in g m -2 yr -1) at twosites where porewater profiles and sediment accumulationrates were measured .

that was resuspended to that input from externalsources was calculated to be 0.66 and 0.30 atSites A and B, respectively . While events of re-suspension may substantially increase the con-centration of particles suspended in the water(> 100%), only the top few millimetres of sedi-ment need to be resuspended to account for theflux of resuspended particles . Thus the remainderof the sediment column is left undisturbed (Rob-bins et al., 1990).

To evaluate the significance of arsenic diffusionacross the sediment-water interface, we calcu-lated this flux using Fick's first law :

F = 4DeaC/8Z,

(2)

where F is the diffusive flux of the element(mg m -2 yr -1), D e is the diffusion coefficient forthe substance (m 2 yr-1), 0 is the porosity of thesediments, and 8C/8Z is the depth-concentrationgradient (mg m - 3 m - 1 ) measured at the bound-ary between the water and the sediments. Meth-ods of estimating each of the variables in the aboveequation are described below .

The water content of the surficial sediments isvery high in areas of sediment accumulation(> 95 % ; Cornett et al., 1989). Therefore, we haveassumed 0= 1 and tortuosity effects are negligible(Li & Gregory, 1974) . We approximated D e bythe molecular self diffusion coefficient calculatedat the in situ temperature by the Stokes-Einsteinrelation (Li & Gregory, 1974) . Several studiessupport the contention that diffusion in the sedi-ment occurs at molecular rates and is only slightlyenhanced by the mixing processes occurring inthe water column (Hesslein, 1980 ; Carignan &Nriagu, 1985) .

The self diffusion coefficient for any ion alsodepends upon the charge and size of the ion .Based upon the Eh, pH and ionic strength of theporewater, we believe that the dominant ionpresent near or at the sediment-water interfacewas H2AsO4 (Ferguson & Gavis, 1972) . Thecoefficient of molecular diffusion for this speciesis 9.05 x 10 - 6 cm2 sec -1 at 25 ° C (Li & Gregory,1974). This coefficient, corrected to the mean an-nual water temperature (8 ° C) was used in allcalculations .

Range Mean Units

Particle mass' 8.8-117 17 g M -2

Trap catch 2 73-1700 730 gm -2 yrBurial3 73-318 160 gm -2 yr -

Site A Site B

External load 600 600Outflow 440 440Deposition 670 670

Resuspension 400 180Net diffusion 890 480Burial 110 60

The final term required to estimate the diffusivefluxes is the concentration gradient of As . Thegradient is scale dependent since it depends uponthe distance between two or more concentrationmeasurements . Dissolved As concentrations weremeasured at 2 cm intervals within the porewaterand approximately 1 .0 m above the mud-waterinterface. We used these porewater concentra-tions measured at 2 cm intervals to calculate thedifference in concentration in the porewater. Toestimate the concentration gradient at the inter-face, we have extrapolated concentrations mea-sured in the porewater to the mud-water interfaceusing linear regression and assumed that the con-centration above the boundary layer at the mud-water interface is equivalent to that measured1.0 m above the sediments . The thickness of thediffusive boundary layer at the mud-water inter-face was estimated to be 750 pm based upon theexperiments of Santschi et al. (1983) .

The porewater concentrations summarized inFig. 3a demonstrate the bidirectional nature ofarsenic concentration gradients in the lake sedi-ments. Arsenic was transported from the regionof high concentrations, 10-20 cm below the mud-water interface, deeper into the sediments and itis also migrating towards the interface and acrossthe mud-water interface into the water column(Table 3) . The diffusive flux of arsenic into thewater column from the sediments (480 and890 mg m - 2 yr at Sites A and B respectively) wassimilar to the external loading of arsenic throughthe inflow (Table 3). The diffusive flux was greaterthan the arsenic fluxes due to resuspension orburial. We interpret these calculations to supportthe hypothesis that back-diffusive remobilizationfrom sediments to water is a significant transportprocess in Moria Lake. A more detailed analysisof the seasonal variation in arsenic fluxes alsosupports this analysis (Diamond, 1990) . Cur-rently, the fluxes of arsenic from the sedimentsinto the water (i .e. the internal loading) are asimportant as the input of arsenic by the MoiraRiver. In the next section, we have generalizedthis picture of the arsenic fluxes using a simpledynamic mass balance model to examine the his-torical trends in sediment-water interactions .

Modelling arsenic dynamics

Relatively large amounts of arsenic have accumu-lated in the bottom sediments of Moira Lake dur-ing the past 150 years . To examine the temporalchanges in arsenic fluxes, we constructed a onedimensional mass balance model of arsenic andparticle transport similar to those used by others(Thomann & Di Toro, 1983 ; Chapra & Reckhow,1983 ; Eadie & Robbins, 1987 ; Robbins et al .,1990; Diamond et al., 1990; Vezina & Cornett,1990). We have assumed that the water columnis well mixed and coupled to a surficial layer ofmixed sediments that is separated from the over-lying water by a benthic boundary layer (Santschiet al., 1983). In the water and in the sediments,arsenic is partitioned instantaneously between thewater and the sediments using the distributioncoefficients measured in this study . Diffusion,particle deposition and resuspension transportarsenic between the water and the sediments usingfirst order rate constants derived from the fluxesdescribed earlier. The mass balance in the water,comprised of 4 terms (inflow, resuspension, dep-osition, and diffusion) is expressed as :

BC,,,/Bt = R • AS/Z - L - C 2 . AP

- De/Zs (Cd - Cpw)/Z+ (C„, - CH )T ,

(3)

where C,,, and C,, are the total concentration ofarsenic in the lake water and in the river inflowrespectively, AP and AS are the concentrations ofarsenic on the particle phase in the water and inthe sediments respectively, and Cd and C,,, arethe concentrations of arsenic in the soluble phasein the lake water and porewater in the mixed layerrespectively. The definition of the other variablesand the values of the parameters used in the sim-ulations are summarized in Table 4 .

Arsenic is transported within the sediment col-umn by bioturbation within the mixed layer,diffusion and sediment accumulation (burial) . Inthe mixed layer, the mass balance equation de-scribing arsenic concentration per unit volume(A 1 ) is :

54 1

542

Table 4 . Summary of parameter symbols (S) and values used in the simulations .

aA1/at= -R-AS/Z+L-Cp-AP+ De/Zs(Cd - CPW)/Z- (De + Eb)(A - A2)/

((Zmix + Zseg )/2) - w - A,

(4)

The first three terms are identical to those in thewater column mass balance. The fourth termsums the mixing and diffusive fluxes from themixed layer to deeper in the sediment columnusing Fick's first law and the final term calculatesthe rate of arsenic burial, ignoring compaction ofthe sediment matrix . Below the mixed layer theburial of particles and the burial and diffusion ofarsenic were described by Eqn . 1 . Arsenic diffu-sion was calculated by correcting the effective dif-fusion coefficient by the distribution coefficient(Lerman, 1979). Then these equations weresolved numerically in finite difference form (e .g .Chapra & Reckhow, 1983) .

All of the simulations predict that the fluxes ofarsenic between the water and the sediments rap-idly approach a steady state if the external load-ing rate is constant. The rapid exchange predictedby the simulations is consistent with tracer fluxesmeasured in situ in short term experiments (e.g .Nyffeler et al., 1986; Santschi et al., 1986 ; Dia-mond et al., 1990). To simplify the interpretation

of the simulations, we have changed the tempo-ral variation in loading to a continuous gaussianinput. This function was varied so that simulatedand measured distributions of arsenic in the lakewater and surficial sediments were similar . Thenwe examined the relative importance of the inter-nal and external loading of arsenic over time .

These simulations predict that arsenic inputinto the water from the sediments has been asignificant fraction (>20%) of the arsenic load-ing throughout the recent history of the lake(Fig. 5). The input from resuspension is more im-portant than the diffusive fluxes during the periodof high external loading. However, during the pe-riod when we studied the lake, all of the fluxeswere very similar in magnitude . The inputs fromthe sediments are predicted to continue duringthe next - 30 years as diffusion and resuspensionregenerate arsenic from the sediments into theoverlying water. During this period, we predictthat internal loading will be much greater thanexternal inputs, and the reservoir of As in thesurficial sediments will delay the decline in ar-senic concentrations in the lake water and controlthe long-term behaviour of arsenic within theMoira lake system . This conclusion is consistentwith the analysis of Cs-137, and PCB compoundsin the Laurentian Great lakes (e.g. Thomann &

S Units Description Value

CP gm- 3 Concentration of particles 3 .90E + 00P yr -1 Particle production rate 8.40E - 00L m3 g -1 yr-1 Nonlinear particle loss rate 3 .60E + 01R gm-2 yr -1 Resuspension rate 5 .50E + 02w myr -1 Sediment accumulation rate 3.00E - 03E,EbZmix

In2 yr -1

mBioturbation coefficientMixed layer depth

2.00E - 012.00E - 02

Z, m Diffusive boundary layer thickness 7.50E - 04DM m2 yr-1 Free solution diffusion coefficient 1.90E-02DENS kg/1 Density of the sediments 1 .25E + 00H2 O Water content of the sediments 9 .50E + 01T yr - 1 Hydraulic flushing rate 2.90E + 00Z m Water column depth 4.40E + 00KDCT 1 kg- 1 Kd of particles in the water 2 .00E + 04KD 1 kg - Kd of surficial sediments 2.00E + 03

TNi E

Q)

X

Ju .Uzw

6000

5000

4000

3000

2000

1000 Iz

-1000

1

1 1. II11940

1950

1960

1970

1980

1990

2000

2010YEAR

Fig. 5 . Fluxes of arsenic simulated by the mass balance model(river input *, resuspension A, and diffusion from the sedi-ments p) .

Di Toro, 1983 ; Eadie & Robbins, 1987; Robbinset al ., 1990). In order to make more rigorousquantitative predictions of future arsenic concen-trations in Moira Lake and more generally, toimprove models of contaminant transportthrough freshwater, we must estimate more ac-curately the size of the contaminant pool withinthe sediments and the rate that it exchanges withthe overlying waters in whole lake systems .

Acknowledgements

This study was funded in part by the NationalUranium Tailings Program . We thank H. Steger,D. R . Lee, and G. M. Milton for critical com-ments. Special thanks to E . 0. Sauk and J. C .Cochrane for assistance in preparing the manu-script .

543

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