Flux of particulate aluminum across the southeastern U.S. continental shelf

Flux of particulate aluminum across the southeastern U.S. continental shelf

Estuarine, Coastal and Shelf Science (1989) 28,327-338 Flux of Particulate Aluminum Southeastern U.S. Continental Herbert L. Windom Skidaway U...

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Estuarine,

Coastal

and Shelf

Science

(1989) 28,327-338

Flux of Particulate Aluminum Southeastern U.S. Continental

Herbert

L. Windom

Skidaway U.S.A. Received

Institute

20June

Keywords:

and Thomas

of Oceanography,

1988 and in revisedform

flux; particulate

P.O.

Box

Across Shelf

the

F. Gross 13687

17 September

Savannah,

Georgia

31416,

1988

Al; shelf; southeastern U.S.

We have determined the concentration of particulate aluminum across the coastal boundary front and the continental shelf of the South Atlantic Bight. We use a simple advection/diffusion model, incorporating particle settling, to interpret our data on the particulate aluminum distribution. By matching modelled distributions of particulate aluminum to measurements, an offshore advection velocity and offshore flux are predicted. Our conclusions are: (1) advection and settling are the major processes affecting cross-shelf particulate aluminum distributions (i.e. diffusion is insignificant); (2) less than 10 percent of the sediments delivered to the South Atlantic Bight by rivers is transported across the shelf by this mechanism; and (3) insignificant amounts of inorganic particles of diameters greater than c. 10 pm are removed from the nearshore region.

Introduction

The cross-shelf transport of particulate matter delivered to the southeastern United States coast by rivers or particles formed in the estuarine-coastal environment is inhibited by a nearshore salinity/density front. Such fronts are a common feature of coastal areas that receive significant freshwater runoff. For areaslike the southeastern Atlantic United States Coast (South Atlantic Bight) where numerous medium size rivers discharge, a coastalfront may extend along shore over a large distance. The zone landward of the front consistsof low salinity, highly turbid water. As a result of the coastalfront fine grain sedimentson the continental shelf of the South Atlantic Bight are confined to the nearshore region, within the frontal zone. Work by Bigham (1973) and Doyle et al. (1968) have shown that this is the only region of the shelf where sediment is presently accumulating. The remaining shelf sedimentsare relict sands (Gorsline, 1963) containing generally less than 0.17, fines (i.e. < 63 pm grain size). The recent/relict sediment boundary is located at c. 5 to 10 km offshore (Pilkey & Frankenberg, 1964; Doyle et af., 1968) and probably represents the approximate mean location of the coastalfront. The physical characteristics and dynamics of coastalfronts have been discussedin some detail by Blanton (1981, 1986). Within frontal zones coastalbaroclinic currents transport low salinity 0272-7714/89/030327

water

alongshore + 12 $03.00/O

in response

to coastal wind

stress. This

confines

the low

@ 1989 Academic Press Limited

328

H. L. Windom & T. F. Gross

salinity water within the zone and inhibits the offshore transport of material. The degree of this inhibition of transport determines the relative importance of the nearshore region asa trap for various materials and thus it is important to quantify cross-front fluxes. The flux of many substancesthat behave conservatively acrossthe coastal front of the South Atlantic Bight (e.g. metals; Windom & Smith, 1985)have been estimated from their relation to salinity. The flux of salt and the relative importance of diffusive and advective processeshas been determined for different wind stress conditions by Blanton (1986) using time seriescurrent and salinity measurementsacrossthe frontal zone. The flux of non-conservative substances, such as those associated with particles, however, has received little attention. During 1985we participated in a multidiscipline field experiment with an objective to estimate the rate of removal of particles from the nearshore region of the South Atlantic Bight and acrossthe inner shelf. The overall goal of this experiment (referred to asSPREX for Spring Removal Experiment) was to evaluate the physical, chemical and biological oceanography of the coastal zone and the inner shelf of the South Atlantic Bight during spring. A review of oceanographic data for the South Atlantic Bight by Atkinson et al. (1983) had indicated that nearshore low salinity water moves northward and spreads offshore during the spring providing for more favorable conditions for cross-shelf removal of freshwater and other materials from the coastalzone. In this paper we present results on the concentration of particulate aluminum, which servesasa tracer of inorganic particles, acrossthe coastalzone front and inner continental shelf of the South Atlantic Bight (Figure 1). We use a simple advection/diffusion model, incorporating settling, to interpret our data on the distribution of particulate aluminum. This model computes the vertically averaged particulate aluminum concentration as a function of distance offshore from the front for given initial particle size distributions and for given offshore rates of advection of water. Finally we use the model to estimate the cross-shelf particulate aluminum flux from the concentration distributions observed during the SPREX experiment. Methods During the SPREX experiment particulate trace metal sampleswere collected in duplicate from near-surface (c. l-3 m) and from near-bottom (c. l-3 m off bottom) along the three transects shown in Figure 1. Only near-surface sampleswere collected at some nearshore stations becauseof weather. Sampleswere collected in 30 1Go Flo bottles. Immediately after sampling, the Go Flo bottles were placed on an apparatus that continually rocked the bottles to keep particles in suspensionduring filtration. The bottles were pressurized with filtered nitrogen gas to force the water through teflon lines to polycarbonate filter holders containing precleaned 0.4 urn Nuclepore filters. All filtration was carried out in a clean bench on board the R/V Cape Hatteras. Filters were digested with HF-HNO, in the laboratory and analyzed for aluminum by atomic absorption spectrophotometry. All results are expressed in massper volume of water filtered after subtraction of a blank which is basedon analysesof ten filters that had been processedassamplefilters but were not used to collect suspendedsolids. Results Particulate

aluminum

concentrations

and distribution

Each transect was sampled twice, at a three day interval. Comparison of near-surface

Flux

of particulate

329

aluminum

32

Figure 1. South Atlantic Bight (inset) and SPREX study area showing which samples were collected for particulate aluminum analysis.

transects

along

and near-bottom samples indicate that the water column is relatively homogeneous with regard to suspended solids (Figure 2). The salinity distribution along the Charleston transect (Figure 3) clearly shows that the water column is vertically homogeneous. During the SPREX experiment the size distribution of suspended sediments (Figure 4) were determined by Coulter Counter on samples collected inside the coastal zone front on each of the three transects for which particulate aluminum samples were collected. Although the size distribution does vary somewhat temporally and spatially, the overall variation is not large. We assume that particulate aluminum is a good tracer for suspended inorganic particles since it is common to the majority of the inorganic phases making up the fine fraction of nearshore bottom and suspended sediments. We further assume that the particulate matter within the coastal boundary zone is dominantly inorganic since particulate organic carbon (POC) is about equal to particulate aluminum and the former represents about 50”,, of the total organic matter while the latter represents less than 10% of the total inorganic matter. Outside the zone biogenic particles become important. Given the above assumptions we expect particulate aluminum in samples collected

330

H. L. Windom Q T. F. Gross

Charleston April

8

transect

-1

April

I

II

-;o:j1 ,:, 1] , , ,:,,,:,j Klawah 8

April

transect

9

transect i

Savannah April

0

IO

20

30

40

50

60

IO /

70

80

0

Distance

April

IO 20

30

40

50

60

13 (

70

80

(km)

Figure 2. Particulate aluminum concentrations versus distance and 0, bottom. Each value is the mean of two analyses.

offshore

for 0, surface

3O0

Figure (upper)

I 15

c

I 30 Dlstonce

3. Cross-shelf salinity and April 12 (lower).

I 45 (km)

distribution



I 60

along

.

-I

the Charleston

transect

for April

7

Flux of particulate

aluminum

Particle

331

dlometer

(pm1

Figure 4. Size distribution of suspended sediments for samples collected inside the coastal zone boundary (i.e. inshore most stations on transects shown in Figure 1). Large dotsrepresentthemeansizedistributionfor--,Cl;-------,C2;----,Kl;----, K2;------,Sl;and-.-.,S2.

within the coastalboundary zone to have size distributions similar to those determined for the total suspendedsolids (Figure 4). Model derivation To model the distribution of particulate aluminum across the inner shelf of the South Atlantic Bight we first divide the inner shelf at the coastalzone front into a nearshore well mixed coastal zone and the region of interest, the offshore inner shelf. On the landward side of this boundary (i.e. within the coastal zone) suspendedparticle levels in the water column are controlled by several processes including river discharges, flocculation, resuspensionand sedimentation. We assumethat the coastal zone acts as a continuous source of material to be transported offshore. Once a parcel of water leavesthe well mixed coastal zone by passingthrough the front, we assumethat there is no additional input of particles since bottom shelf sedimentsoutside the coastalzone do not provide a source(see introduction). The depth integrated concentration of particulate aluminum outside the coastal zone is therefore assumedto be controlled by gravitational settling, advection and diffusion such that the change in the depth integrated mass,M, of the particulate aluminum concentration, C(Z), in the water column with time, t, and distance, X, offshore is given by: (1)

where: M =

z s

C(zkk 0 U is the rate of advection, w is the fall velocity of the particles, Z is the water depth and Kh is the horizontal mixing coefficient (i.e. eddy diffusivity).

332

H. L. Windom & T. F. Gross

The settling term in the unintegrated equation (1) for aluminum concentration, zu?C,’ 82, integrates to w [C(Z)- C(o)]. The concentration at the bed C(Z) is set to zero to represent the capturing state. The rest of the water column is assumedwell mixed in the vertical and thus M = Z C, therefore w [C(Z) - C(o)] = w M/Z. We assumein the model that depth increaseslinearly offshore. As a parcel of water moves offshore water depth increasesresulting in a dilution of particulate aluminum and a slower clearing rate. The change in depth can be approximated by

z = z, + sx,

(2)

where x is increasing distance offshore, perpendicular to the coast. The coastalzone front is taken to be at x, = 0 and the depth at the front is Z,. S is the bottom slope. We now follow a parcel of water that is advected away from the coastal front along a transect perpendicular to the front. The total change in the massof particulate aluminum in this Lagrangian water parcel with time is now due only to removal by setding and horizontal diffusion 2 dM (3i -= -M;++ dt At a distance, dx, offshore the decreasein massof particles in a specific size range will depend on the time, dt, required to advect a water parcel that distance. For a given rate of advection, U, dx 4! dt=LI. In this manner the time dependency of the Lagrangian equation 3 is changed to space dependence. Substituting equation (2) and (4) into equation (3) gives

(5)

d2M dM 1 -=-MA+&-. dx U[ dx” z, + sx Since this equation is difficult to solve with the horizontal diffusion term present we will first demonstrate with scaling arguments that the horizontal diffusion plays a small role in the South Atlantic Bight. Then simplifications can be madeto give an analytic solution for the distribution of particulate aluminum. To show that the diffusion term is unimportant the three terms of equation (5) will be estimated. Near the source, at a depth Z, gradients are largest and diffusion will be greatest. Initially we can assumethe advection and fall velocity terms are the major balanceasmodeled above. This assumptionwill be shown true if the diffusion term proves to be small. The scaling of the derivative dM/dx can be evaluated from the balanceof advection and fall velocity terms:

1

dM

I

w

(6) aczM. dxuz, + sx The length scaleof the horizontal gradient is thus, UZjw. The scaling of the major balance of advection and fall velocity terms is (taking Z= 10 m and w = 0.01 cm s-l) ---M

M=UEzM=

0.01 cm s-’ 1000 cm

M = 10-5sm1M.

(7)

The horizontal diffusion term is represented by the mixing coefficient Kh in equation (5). IZh is primarily due to the offshore tidal velocity scale, Utlde, and the tidal excursion

Flux

of particulate

333

aluminum

length scale, Ltide. The approximate maximum value of Kh is therefore Urlde Lcide= (5 cm sP ‘) (50 000 cm) = 25 x lo4 cm2 s-I. Blanton (1986) calculated diffusion coefficients for the cross-front flux of salt to be of the order of 10’ to lo3 cm2 s-l. The importance of horizontal diffusion is therefore greatly exaggerated here to demonstrate its small contribution. The length scale of the horizontal gradient will be UZjw as it was for the advection term. The scaling for the diffusion term is then d2M 5, -x dx”

-2

M = 25 x 104cm2sP’

0.01 cm SC1

2

5cms-‘1OOOcm

= O,lO x 10-5s-1M The horizontal diffusion term is therefore only 0.10 the advection or fall velocity terms. This is a worst case estimate using a large horizontal eddy diffusivity and in the region of largest gradients. The order of the three terms depends on the fall velocity. For larger particles the near shore gradients are larger and diffusion will apparently spread out the distribution. However, the concentration and gradient will drop rapidly due to the fall velocity and the offshore distribution will be little affected by diffusion. The smaller particles will mix offshore and be transported greater distances. The transport will act to reduce gradients and again diffusion will be less efficient in offshore transport than advection. A simple analytical solution to equation 5 is now possible by neglecting the diffusion term. To compare the model results with the data we divide the population of particles making up the total particulate aluminum into N particle size intervals, each representing an equal portion of the total mass, mi= M/N. For each such interval the particle diameter ranges from d, to di+r, where i goes from 1 to N and d, and d,,, are the minimum and maximum diameters of the population of particles, respectively. The mean particle diameter of each interval, 4, is given by the following equation ai = 0.5 (d, + d,,,).

(9)

A mean fall velocity, wi, can be determined for each size interval by use of the Stokes fall velocity equation. The simplified equation for each size class is then

(10) which integrates to give Inor

m;(x)

= - 2

In (1 + Xx/Z,)

(114

mi(xJ m;(x) = m&)

(1 + Sx/z,>-“~‘us

(lib)

where W+(X) and m,(x,) are the mass of particles between diameters of di and di+ r at distance x offshore and at the coastal zone boundary front (x0 = 0), respectively. Since the total mass, M(x) at distance x offshore is equal to the sum of the masses of the N size intervals and m,(xJ = M(x,)/N, we have

M(x,) ;h’ (1 + Sx/z,)-““cs

M(x) = - N

I 1

(12)

334

H. L. Window

0

Q

T. F. Gross

IO

20

30

40 Drstance

50

60

70

80

(km)

Figure 5. Results of model calculations (Eq. 10) for mean size distribution given in Figure 4 and for different values of U. Shaded areas for cases, U = 1 and 10 cm s I, show the effect of variations in size distributions as shown in Figure 4.

Using equation (12) we can now calculate the expected particulate aluminum massof a water column at distances offshore if the size distribution of the source (i.e. particulate aluminum size distribution inside the front) is known. For this we take the mean size distribution of the suspendedsediments (indicated by large dots in Figure 4) asrepresentative of the source and divide this into ten size intervals (increasing the number of intervals does not change results significantly for this case). Rearranging equation (12) we then calculate the massof particulate aluminum as a percentage of the initial mass,M(x,), with distance offshore using different values of advection (U= 1,2,3,4,5 and 10 cm s-l) and a bottom slope, S, of 0.5 m km-‘. The depth, Z,,, at the coastal zone front (x, = 0) is assumedto be 5 m. The results, plotted in Figure 5, are basedon the assumption of steady state; M(x,) and U are constant over the time interval neededfor a water massto move from x, to x. Application

of model to estimate particulate

aluminum

fluxes

Although the steady state assumption in the model (i.e. the particulate aluminum concentration at any point, x, along a transect doesnot changewith time) certainly doesnot hold, the data suggestthat variations are small enough that the model should still be applicable. By converting the data from particulate aluminum concentrations to total water column massof aluminum (in mg m’) the relative masscan be plotted versus distance offshore (Figure 6). Using the inshore most station as the coastal zone front, the distribution models shown in Figure 5 were compared to the data to determine the best fit for different values of U. The data appear to fit the model well enough to conclude that the advection of particles acrossthe shelf is between c. 2-4 cm SC’. Using the values for the range in advection determined from the model we calculate the flux of particulate aluminum at a point along each transect. We choosethe 40 m isobath, the offshore limit of our data, to calculate fluxes (Table 1) since these probably give reasonable

estimates

of the maximum

amount

of particulate

aluminum

leaving

the shelf.

The South Atlantic Bight receives the discharge of nine rivers over approximately 400 km of coastline. The total averagedischargeis c. 2000 m3 s- ’ and the averagesuspended

Flux qf particulate

aluminum

Charleston

r

transect

b ‘0°:L

3

IO

U=4cm

5-l

April

335

l

l .

8 0 II l

0.1

Klawah

April

transect

9’2 12*

Sovonnah

transect

IOO‘O-u:zcm \\ s-1 a . I-

0 I

0.1+ 0

April , IO

0

100 13. I 20

I I 30 40 Distance

I 50 (km)

/ 60

I 70

E

Figure 6. Relative mass of particulate aluminum versus distance offshore. point is based on the mean of the near surface and near bottom concentrations.

1. Particulate

TABLE

Transect

Cl c2 Kl K2 Sl s2

aluminum

flux across the 40 m isobath

Particulate aluminum concentration (mgm ‘)

Flux (mg m--’ s ‘)

0.6 0.3 0.4 0.3 0.1 o-3

0.48-0.96 0.24-0.48 0.32-0.64 0.24-0.48 0.08-0.16 0.24-0.48 Mean

0.26-0.52

Each data

336

H. L. Windom & T. F. Gross

March

April

July

May 1985

Figure 7. Alongshore wind stress component from wind data collected Savannah and Jacksonville (from Windom l? Blanton, submitted).

Ll=2cm

100

at Charleston,

s-’ TAd,

i

IO 8 5 a, .!$ c 0.1T

Ad,

0.1

0

-)

IO 20

'OrAds 30

I 40

Distance

I 50

I 60

I 70

80

(km)

Figure 8. Relative mass of particles within a given size interval versus distance. Values were calculated using equation (8) for the seven smallest size intervals from the mean size distribution given in Figure 2.

sediment load was determined over a one year period by Windom (1975) to be c. 18 g m’. The mean flux of suspended sediments to the South Atlantic Bight is estimated to be c. 3.6 lo4 g s-l. This value is probably low since it is not weighted for the correlation of load with discharge. South-eastern U.S. rivers show a generally positive correlation

Flux

of particulate

aluminum

337

between suspended load and discharge (Meade, 1982). Our estimate of offshore flux of particulate aluminum for the 400 km coastline is c. l-2 lo2 g s-l. Assuming that the suspended sediments entering the South Atlantic Bight from rivers contain lOa& aluminum, the total sediment flux based on aluminum flux observed during the SPREX experiment predicts that less than 109; of the riverine particulate matter is transported across the shelf. Discussion The estimated flux of particles given above is based on results of studies conducted during a brief period in the spring 1985. It is tempting to conclude that these results reflect springtime transport conditions when in reality the transport observed during the SPREX experiment was dominated by a strong northward, alongshore wind impulse that just preceded the time of the SPREX cruise (Figure 7 from Windom & Blanton, submitted). Under these conditions transport of particles is clearly more efficient than during summertime quiescent conditions. During wintertime, however, wind conditions associated with each of the many cold fronts that cross the coast may result in a more efficient transport regime than observed during SPREX. Each set of climatic/seasonal conditions must be understood before good cross shelf particle flux estimates can be made. For this purpose different sets of conditions must be evaluated to determine how they affect the source term (i.e. suspended sediment conditions within the coastal boundary zone) and cross shelf transport. The model presented above provides a basis for making these evaluations. We draw one final conclusion from the application of the model to particle transport across the continental shelf of the South Atlantic Bight. Because the model considers the removal by size interval we can use it to determine cross shelf transport of different size particles for any value of advection. Using the range of values for advection (2-4 cm s-‘) estimated from our data it appears that only inorganic particles of diameter less than c. 10 pm can be efficiently removed from the nearshore region (Figure 8). Acknowledgements We thank Dr. G.-A. Paffenhofer for providing particle size analysis data and Ralph Smith, Jr. who conducted the particulate aluminum analyses. We also thank Ms. Dannah McCauley for typing the manuscript and Suzanne McIntosh for providing all the art work. This work was supported by the U.S. Department of Energy (Grant No. DE-FG09-86ER60435). References Atkinson, L. P., Lee, T. N., Blanton, J. 0. & Chandler, W. S. 1983 Climatology of the Southeastern United States Continental Shelf Waters,3ournal of Geophysical Research 88,4705-4718. Bigham, G. N. 1973 Zone of influence-inner continental shelf of Georgia,J. Sed. Per. 43,207-214. Blanton, J. 0.198 1 Ocean currents along a nearshore frontal zone on the continental shelf of the southeastern United States,Journal of Physical Oceanography 11, 1627-1637. Blanton, J. 0. 1986 Coastal frontal zones as barriers to offshore fluxes of contaminants, Rapport of ProcisVerbaux des Rinuniuns. Conseill’ermanent Internationalpour I’Exporation de la Mer. 186,18-30. Doyle, L. S., Cleary, W. J. & Pilkey, 0. H. 1968 Mica: Its use in determining shelf-depositional regions, Marine Geology 6,381-386. Gorsline, D. S. 1963 Bottom sediments of the Atlantic shelf and slope off the southern United States,3ournal of Geology 71,422-440.

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& T. F. Gross

Meade, R. H. 1982 Sources, sinks and storage of river sediment in the Atlantic drainage of the United States. Journal of Geology 90,235252. Pilkey, 0. H. & Frankenberg, D. 1964 The recent-relict sediment boundary on the Georgia continental shelf. Bulletin of the Georgia Academy of Science 22,73-78. Windom, H. L. 1975 Heavy metal fluxes through saltmarsh estuaries. In: Estuarine Research, Vol. 1 (Cronin, L. E. ed.), pp. 137-152. London: Academic Press. Windom, H. L. & Smith, R. G. 1985 Factors influencing the concentration and distribution of trace metals in the South Atlantic Bight. In: Oceanography of the Southeastern U.S. Continental Shelf(Atkinson, L. l’., Meniel, D. W. &Bush, K. A. eds) p. 141-152. American Geophysical Union. Windom, H. L. & Blanton, J. 0. 1989 Freshwater flux across the continental shelf of the South Atlantic Bight during spring. (submitted to Continental Shelf Research).