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COMPUTER S IMULATI ON OF DDT DI STRI BIrrI ON IN PALO S VERDES SHELF SEDIMENTS Bruce E. Logan and Robert G. Arnold University of Arizona and Alex Steele Los Angeles County Sanitation Districts ABSTRACT Prior to impos ition of effective source control meas- ures in 1970, large quantities of DDT were discharged to the Los Angeles County municipal sewer system and subsequently to the Pacific Ocean. among sediments of of the DDT lies 10 Much of this material accumulated the Palos Verdes shelf. While the bulk to 40 cm below the sediment surface, its fate may be affected by future wastewater treatment at the Los Angeles County's 385-mgd, Joint Water Pollution Control Plant (JUPCP). To assess the potential impact of JWPCP secondary treat- ment requirements on shelf sediment quality, processes that may affect distribution of chemical tracers among those sedi- ments (background sedimentation rate, effluent-related solids contributions, sediment mixing, and diffusive trans- port through pore waters) were incorporated in a mathemati- cal model. Because physical mixing substantially affects sur- ficial concentrations and the vertical distribution of DDT at the 60-m depth contour, model projections of surface sed- iment quality at the most heavily contaminated sites are sen- sitive to projected effluent solids concentrations and thus JWPCP treatment decisions. Dredging and capping do not rep- resent physically or economically feasible remediation stra- tegies at this site. The work described illustrates how empirical models of contaminant fate can be used to (1) simp- lify or avoid uncertainties associated with some mechanistic models, and (2) serve as a basis for management decisions. INTRODUCTION Indicators of biological quality among benthos of the Palos Verdes shelf are sensitive to chemical characteristics of surface sediments (Word, 1978; Sherwood, 1976; Oshida and Wright, 1976; Cross, 1984~. 178

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179 Species composition and primary feeding strategies among benthic inver- tebrates are functions of both sediment organic content and local sur- face concentrations ~ top 5 cm) of hazardous compounds including trace metals, total DDT, and PCBs (Stull et al., 1986~. Despite uncertain- ties caused by statistical correlations among individual chemical param- eters, the importance of controlling surface concentrations of DDT in sediments of the Palos Verdes shelf has been accepted; Prior to a ban on its disposal within the Los Angeles County municipal sewage collec- tion system in about 1970 (Norman Ackerman, Supervisor, Oceanographic Monitoring Activities, LACSD, personal communication), DDT was held responsible for endangerment of the California brown pelican (Keith et al., 1970; Risebraugh et al., 1967, 1971~. The Los Angeles County Sanitation Districts (LACSD) provides par- tial secondary treatment (200-mgd secondary treatment capacity) for approximately 360 mad (136,300 m3 d- ~ of domestic and industrial wastewater at the Joint Water Pollution Control Plant (JWPCP) in Car- son, California. Effluent, including some 150 metric tons of suspended solids per day, is discharged via a system of ocean outfalls to waters of the Palos Verdes shelf. During the last 15 years, JWPCP effluent quality has shown marked improvements, in terms of solids emissions and concentrations of specific contaminants including total DDT (Figure 2), in response to improved treatment and solids handling at JWPCP and implementation of source-control measures on tributary industries. Much of the DDT that was discharged to the LACSD sewer system prior to 1970 reached the coastal waters and sediments off the Palos Verdes peninsula. Due to its persistence, there are residual links to environ- mental quality and human health--muscle tissue concentrations of DDT exceed FDA limitations in local populations of white croaker and other bottom-feeding species (Gossett et al., 1982, 1983~. Surface sediment DDT concentrations appear to drive fish tissue values, as opposed to the DDT mass emission rate from the Whites Point outfall system (Young et al., 1988~. cat cat an to - FIGURE 1 The Palos Verdes shelf in relation to the Palos Verdes Peninsula and JWPCP. Positions ~ and depth of the LACSD outfall O system and sediment monitoring stations are as indicated . ~1 0 1 2 ~ \ Miles Depth in Meters ~ I 118 30 LONGITUDE 118 20 so

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180 400 r 2.0 350 _ 300 1.5 _ 250 _ 200 - 1.0 _ 150 _ Coo - 0.5 _ FIGURE 2 Summary of JWPCP mass emissions 50 _ records to total solids, _ _ DDT, and total flow. - 106 5 4 jo3 102 101 _ ~ _ ~ 10 1 1 1 1 1985 1965 1945 1925 1905 YEAR I DDT 1la/ka SS Mton/yr _~ FLOW mad Sediment quality on the Palos Verdes shelf is a function of physi- cal and chemical processes that are imperfectly understood. These processes potentially include sedimentation, bioturbation by benthic infauna, periodic resuspension by bottom currents or wave activity, and chemical diffusion. Following implementation of effective source- control measures for DDT in the early 1970s, the bulk of the sediment DDT on the Palos Verdes shelf was buried under less contaminated sedi- ment of both natural and sewage-related origin. Recent sediment pro- files (Figure 3, for examples suggest that the bulk of sediment DDT lies buried between 10 and 40 cm below the surface. The contribution of effluent-related particulates to the overall local sedimentation rate is not well established. The background sedi-- mentation rate (independent of outfall particulates) has been variously estimated at 10 to 200 mgKcm~ Kyr~ (Hendricks, 1984), perhaps in response to variations in local coastline stability, and the fraction of solids discharged from the Mites Point outfall system that is retained on the Palos Verdes shelf has been estimated at 0.01 to 1.0 (Myers, 1974; Hendricks, 1982~. There is no consensus regarding the importance of periodic sediment resuspension as a determinant of contaminant profiles. Hendricks (1978, 1982, 1984, 1988) modeled the fate of chemical tracers in Palos Verdes sediments by combining a solids deposition model designed to yield the discharge- and current-dependent pattern of particulate fluxes to the shelf with a sediment resuspension model that produced time-dependent profiles of select contaminants in the Whites Point sediments. Hendricks' work identified areas of theoretical inadequacy and data gaps, which must be addressed before mixing of marine sediments can be addressed mechanistically. At present, it is impossible to address adequately the following areas of uncertainty: 1. potential interdependence of sediment resuspension parameters (resuspension mass, resuspension frequency, and time between

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181 50.0 40.0 30.0 3 o CD J o 20.0 10.0 0.0 Station 8C 107 DATA 1 o6 MODEL r 10;' ~ On 104 103 ~ 102 _ ~ 101 . 1 1 1 1 1 0 10 20 30 40 50 CORE DEPTH cm Figure 3a 60 0 Station 8C ~ DATA MODEL ~MIX/DIF _ 10 1 it, 15 30 45 60 75 90 CORE DEPTH cm Figure 3b 50.0 Station 6C Station 6C 10/ 40.0 - c~ 30 0 - o oh g 20.0 10.0 o.e MODEL DATA 1 o6 105 I' 1 04 - C] ~ 102 ~ 1o1 ) 1 1 1 1 1 1 10 0 10 20 30 40 50 60 CORE DEPTH cm Figure 3c - ~ DATA - MODEL - _ MIX/DIF I ~ I . 1 1 1 0 15 30 45 60 75 90 CORE DEPTH cm Figure ad FIGURE 3 Calculated and observed concentrations of volatile solids or DOT in Palos Verdes sediments among monitoring stations along the 61-m depth contour. Volatile solids concentrations were calculated using the basic sedimentation model without considering surface mixing or diffusion. DDT profiles were calculated using the sedimentation/mixing model. Model parameters used in calculations represented here are summarized in Table 1. In all cases, the solid "data" line represents 1985 LACED monitoring data; the broken "model" line represents best-fit results using the basic sedimentation model; and the broken "mix/dif" illustrates the best-fit model calculations when mixing and diffusion mechanisms are included.

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182 50.0 40.0 Station 3C 10 DATA _ 106 MODEL _ 105 ~, 30.0 _ ~ 104 O ~ 5 20.0 _ ~ 103 o 10.0 <~~ 101 0.0 ~ I ~ ~ ' 10 0 10 20 30 40 50 60 CORE DEPTH cm Figure Be 50.0 Station OC Station 3C _ _ DATA _ _ MODEL - ~ MIX/DIF 1 1 \1 1 0 1 5 30 45 60 CORE DEPTH cm Figure of 107 Station OC 75 ~ DATA MODEL 40.0 _ - MODEL 1 o6 _ MlX/DIf ~ 105 c Ha) 30.0: == 104> h 5 ~ 102 ~ 0.0 ~ 1 1 1 1 1 10~ ~ ~ t~ 1 1 1 1 0 10 20 30 40 50 60 15 30 45 60 75 90 CORE DEPTH cm Figure 39 FIGURE 3 Continued. _~ DATA CORE DEPTH cm Figure ah resuspension and redeposition) and the ratio of effluent- related to natural particulate material among local sediments, 2. biological determinants of sediment resuspension rates, 3. the dynamics of a sediment surface layer approximately 1 mm thick, which may be subject to frequent short-duration resus- pension events prior to stable incorporation into bulk sedi- ments, and 4. aggregation processes among biologically active surface sediments.

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183 TABLE 1 Summary of Best-fit Parametric Values Resulting from Calibra- tion of the Sediment Deposition/Mixing Model across the Palos Verdes Shelf Stationa Background sedi- ~ Effluent Local diffu- Depth of mix- (depth) mentation rate solids reach- sion coeffi- ing zone (cm) (m, dry wt ing grid tied cm /yr) location (cm /see) 8C(61m) 400 0.5 10-8 6 6C(61m) 500 0.5 10-8 6 3C(61m) ' 500 0.2 10-8 4 oC(61m) 500 0.01 10-8 6 6A 200 0.075 10 8 4 NOTE: aStations correspond to those indicated in Figure 1. LACED and the U.S. Environmental Protection Agency (EPA) are now forced to evaluate the merit of imposing an additional 80 percent reduc- tion in suspended solids emissions by establishing full secondary treat- ment requirements for JWPCP. It has been suggested that this action could result in gradual reemergence of previously buried DDT and other effluent-related contaminants for which DDT can serve as tracer. Resi- dual uncertainties associated with mechanistic, state-of-the-art sedi- ment models preclude their use for prediction of Palos Verdes surface sediment quality characteristics as a function of the projected treat- ment level at JWPCP. Here we apply an empirical approach to sediment quality modeling on the Palos Verdes shelf in order to avoid scientific uncertainties that have frustrated more mechanistic treatments. We have developed a ser- ies of sediment models of increasing complexity in order to evaluate the importance of specific processes, or classes of physical processes, as determinants of sediment contaminant profiles. The background sedi- mentation rate and fraction of discharged solids that reaches the sedi- ment grid are treated as fitted parameters (selected to reproduce local sediment profiles of volatile solids and DDT) as are sediment inter- stitial dispersion coefficients and mixing parameters in higher order models. Model results include surface sediment concentrations of DDT as a function of projected treatment level (existing level, full secondary, zero discharge, eta). at JWPCP. METHODS Deposition Model (Order 1) The procedure for calculating sediment profiles of specific contam- inants is described below and summarized in an appendix to this report.

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184 The Palos Verdes shelf was divided into a two-dimensional (horizontal) grid. The background sedimentation rate and fraction of the JWPCP effluent solids deposited in each grid section were independently esti- mated. Effluent-related solids were divided into volatile and nonvola- tile fractions based on JWPCP monitoring records. The biodegradable fraction of effluent solids was assumed to be completely oxidized in the water column prior to deposition. All solids destroyed in this ~ -~ ~ ~ ~ ~ ~ ~ ~ - Residual discharge-related solids were assumed to be refractory, as were solids of natural origin that reached the local sediments. Necessary measurements and parameter estimates included the record of JWPCP solids emission rates dating to 1935 (Figure 2), the fraction of discharged solids that are volatile, and the percentage of volatile solids that are refractory in nature. With this information, the dry mass of solids that reached the shelf sediments during each year of record was calculated as a function of position on the shelf. The com- All solids destroyed in this fashion were assumed to come trom the volatile traction. _ putational procedure also yielded an estimate of the volatile solids fraction in the sediments for comparison with measured concentrations. The total mass added to the sediment column during each year was dependent upon an empirical relationship between sediment volatile awl i Ac! =~ m^; c! - ll - = ^^r~t~=rit~ {Ar~r`~=Aiv) ~_~_~ ~~ ~~_~_. A- Or--. On the basis of the total mass addition and the calculated (weighted average) sediment density, it was possible to compute the thickness of an incremental layer of sediment that accumulated in response to natural and effluent-related particle deposition during each year. The position-dependent increment of mate- rial predicted to have accumulated on the Palos Verdes shelf during the lifetime of the Whites Point discharge (in the absence of resuspension and mixing) was developed by integrating the calculated annual contribu- tions. The computational procedure also yielded depth-dependent esti- mates of volatile solids and moisture concentrations. These were com- pared to profile data collected at several grid locations across the shelf to determine goodness-of-fit. By varying input parameter values, it was possible to select the most appropriate local background sedimen- tation rate and fraction of effluent solids deposited within specific grid boundaries. In order to predict sediment profiles of specific effluent-related contaminants, results of the foregoing procedure were combined with measurements or estimates of annual mass emission rates (MERs) for the contaminants of interest. ~ ~ ~ ~~~ ~ ~ ~ --- In mode Lang ~VT, it was assumed that (ly DDT was uniformly distributed (by mass) among effluent solids, and (2) dis- charged DDT was entirely refractory in nature. Only total DDT was modeled in this fashion. Sediment computations yielded depth-dependent DDT concentrations in units of mg DDT per kg of dry solids. Annual DDT mass emissions and other input data are summarized in Figure 2. Fitted parameters in the initial modeling phase included only the background sedimentation rate and the fraction of effluent solids that is deposited in specific sectors of the sediment grid. Results of LACED work using Hendrick's models were used to suggest appropriate limits for parameter ranges. Grid sampling stations at which the mass contribution of effluent solids is modest (in comparison to background sedimentation), also provided an initial estimate of the background sedimentation rate.

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185 Sediment profiles of volatile solids, moisture content, and DDT con- centration were developed in this manner for each sediment grid position at which LACSD measured profile characteristics in 1985. Background sedimentation rate and deposition of effluent-related solids were adjusted to reproduce the volatile solids profile (depth and magnitude of elevated volatile solids concentrations) to the extent possible. Mixing Model (Order 2) Perceived shortcomings in the level-one (deposition) model were addressed by adding surface-mixing and DDT-dispersion components to the computation of sediment profile characteristics. While the procedure was limited to calculation of depth-dependent DDT concentrations, it could be adapted to predict profile concentrations of any conservative contaminant for which there is an adequate base of effluent data. Computational procedures for the mixing model included those of the deposition model mass balance, altered to account for surface mixing and vertical diffusion of DDT throughout the sediment column. Diffu- sion was incorporated by dividing the sediment profile into 2-cm com- partments and permitting concentration-driven transport between adja- cent compartments during specific finite time intervals. The 2 cm represents both the depth interval for chemical determinations in LACSD sediment cores and a practical compartment thickness for the diffusion computation. A well-mixed zone, defined to consist of an arbitrary num- ber of the uppermost 2-cm compartments, received the entire input of deposited material during a given time interval; complete mixing was assumed over the time necessary to add 2 cm to the overall profile thickness. At that point, a new compartment was created at the top of the sediment core, and a 2-cm compartment was pushed below the mixing zone. Initial estimates of a molecular diffusion coefficient were developed from the literature of mass transport through porous media and later fitted using 1985 DDT profile data from Figure 1 monitoring stations. Sediment Quality Projection Parameter estimates from the mixing model were used to project sedi- ment quality characteristics as a function of the anticipated JWPCP sus- pended solids MER. Treatment scenarios investigated and corresponding solids emissions follow: Treatment Level No change (partial secon- dary treatment) Full secondary Zero discharge Reevaluation of treatment resulting in 2x solids MER Suspended solids MER (10 MT/yr) (assumed constant from 1987 to 2005) 0.40 0.10 0.01 0.80

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186 RESULTS Deposition Model A summary of fitted parameters corresponding to each of the core sampling stations is provided as Table 1. A comparison of best-fit cal- culations (deposition model) and measured (198S) DDT profiles at 61-m monitoring stations is included within Figure 3b, 3d, 3f, and 3h. A statistical measure of goodness-of-fit has not yet been incorporated into the model structures, so model parameters were visually deter- mined. Order-one model calculations and sediment measurements of volatile solids and DDT concentrations were within reasonable agreement at all 61-m monitoring stations along the Palos Verdes shelf. However, 1985 surface sediment concentrations of DDT were uniformly high relative to model calculations, suggesting that addition of a mixing mechanism to the deposition model would improve its performance substantially. Mixing Model A summary of best-fit parameter estimates (deposition/mixing model) for stations along the 61-m contour is provided in Table 1. Estimated background sedimentation rates are nearly uniform across the shelf (400-500 mg/cm -yr) while the local contribution of effluent-related solids varies by a factor of 50. Beyond the shelf, the background sedimentation rate shrinks rapidly. In all cases, the local diffusion coefficient for best fit was 10- /sec. The depth of the mixing zone was 4-6 cm. Calculated and measured profiles of volatile solids and DDT concentrations for stations along the 61-m depth contour are provided as Figure 3 (a-h). DDT profiles corresponding to the diffusion (no-mixing) model are included to illustrate the importance of surface-mixing to development of an effective sediment model. Model Predictions The calibrated sedimentation/mixing model was utilized to project sediment profiles of DDT concentration along the 61-m depth contour. Results are summarized in Figure 4 (a-d) and Table 2. Individual pro- files correspond to JWPCP treatment alternatives ranging from zero dis- charge to a doubling of the current JWPCP suspended solids, mass emis- sion rate. The projected year-2005 surface concentration of DDT at station do is independent of JWPCP treatment level. At the other extreme, the model indicates that initiation of full secondary treat- ment will produce year-2005 surface concentrations of DDT at station 6C that are almost 75 percent higher than those that would result from no additional treatment. In all cases, the predicted year-2005 surface concentrations of DDT are much lower than current levels; there are significant, treatment-dependent differences in those projections.

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187 107 _ _ 1o6 C 105 :l, cl 1 03 1o2 1o1 10 107 1o6 ~ 105 t:n At. 1 03 1 0Z . 10] loo 1n7 1o6 ~ I;\ call 33 KNk/~\ ~ 1 1 1 1` 1 10 ~ 1 ~ 1 ~ 1 0 15 30 45 60 75 90 0 15 30 45 60 75 90 CORE DEPTH cm CORE DEPTH cm Figure 4a Figure 4t 1 _ 10/ _ _ , ~ 1 g85 2005 ~6 c _ 105 Ha\ en 1 04 103 1o2 1ol ~ F . ) ~ 1 1 1 1 ~r 1 10~ 1 1 1 1 1~\ 1 0 15 30 45 60 75 90 0 15 30 45 60 75 90 CORE DEPTH cm CORE DEPTH cm Figure 4c Figure 4c FIGURE 4 Year 2005 projections of sediment DDT concentrations at monitoring station 6C (Figure 1) as a function of depth and treatment level or solids removal efficiency at JWPCP. Corresponding solids MERs are summarized in the text. 4a. No change scenario. Continuation of partial secondary treatment at JWCPC. 4b. Full secondary treatment at JWCPC. 4c. Zero discharge alternative. Hypothetical elimination of ocean discharge via the Whites Point outfall system. 4d. Modification of JWPCP treatment which results in a solids HER 2x the present (1987) level. Doubling the solids mass emission rate is predicted to lower the year-2005, surface sediment concentration of DOT by a factor of four relative to the secondary treatment alternative.

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188 TABLE 2 Projecteda Year-2005, Surface Sediment Concentrations of DDT along the 61-M Depth Contour of the Palos Verdes Shelf Current No change 2x the surface Zero Full (Partial current concen- dis- secon- secondary) suspended StationC tration charge dary treatment) solids MER 8C 11,500 4,000 3,500 2,100 800 6C 9,500 2,200 1,900 1,100 500 3C 3,500 550 500 360 240 dC 780 230 230 230 230 NOTES: aProjections are based on the sedimentation/mixing model. ball figures are in mg/dry kg of sediment. CStation locations are indicated in Figure 1. DISCUSSION Sensitivity In order to demonstrate model response to variation among fitted parameters, results of representative sensitivity analyses are pre- sented in Figure 5 (a-h). Sediment volatile solids concentrations res- pond to variation in both background sedimentation rate and relative size of the outfall-related solids contribution. DOT profile calcula- tions were compared to measured values at station 6C to assess model sensitivity to variation in the molecular diffusion coefficient and depth of the mixing zone. For each of the four parameters tested, appropriate profiles (volatile solids or DDT) resulting from both arti- ficially high and low parameter estimates are presented. Results indicate that the sedimentation/mixing model is reasonably sensitive to selection of the background sedimentation rate, although a 50 percent increase in background sedimentation (Figure 5b) did not substantially affect the quality of fit between calculation and meas- urements. A 50 percent decrease in the assumed natural sedimentation rate (Figure 5a) results in unrealistically high volatile solids con- centration. Volatile solids calculations are very sensitive to change in the relative effluent solids contribution at station 6C. A 40 percent decrease in discharge-related solids (Figure 5c) provides a marked decrease in profile depth; an increase of similar magnitude (Figure Sd) results in overestimation of the sediment organic content. From the sensitivity of profile depth calculations to the local flux of effluent-related solids, it is apparent that the Whites Point

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50.0 40.0 - - cn C, 30.0 J o an IIJ ~ 20.0 o 10.0 50.OI DATA _~ MODEL 40.0 - ~ 30.0 ~ 111 -r ~ ~ 20.0 ~ O -0 - ~ 10.0 DATA MODEL \::; 0.0 ,, ~ ~ ~ ~ 1 1 0.0 I I I 1 1 ~ 0 10 20 30 40 50 60 0 10 20 30 40 50 60 CORE DEPTH cm CORE DEPTH cm Figure 5a Figure 5b 50.0 _ 50.0 _ - DATA _~ DATA 40.0 MODEL 40.0 _ - MODEL - , 30.0 _ o n J ~ 20.0 o 10.0 0.0 - O 30.0 oh llJ = S g 20.0 ~ 10.0! 1 1 1 1 0 10 20 30 40 CORE DEPTH cm Figure Sc it' I I 0.0 1 1 1 1 1 1 50 60 0 10 20 30 40 50 60 CORE DEPTH cm Figure Ed FIGURE 5 Analysis of parameter sensitivity. Comparison of model cal- culations and 1985 sediment profiles of volatile solids or DOT concen- tration at monitoring station 6C (Figure 1) in response to systematic variation in model parameters. In all cases, the solid "data" line represents 1985 LACED monitoring data; the broken "model" line repre- sents results of the sedimentation (no mixing) model calculated using the parametric values summarized below; and the broken "mix/dif" line represents results of the sedimentation/mixing model corresponding to the parameter estimates given.

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190 10r ~ bolt 105 y 1 04 3 10 1o2 1o1 1oo 1n7 ~ + DATA 107 _ MODEL Hi_ MIX/DIF 1 o6 ~ \L f 105 r', 1 04 c, 10 - ~ DATA MODEL ~ MIX/DIF :\\ 101 _ 1 1 1 1 1 1 10 1 1 1 0 15 30 45 60 75 90 0 15 30 45 60 75 90 CORE DEPTH cm CORE DEPTH cm Figure Se Figure 5f 102 ~ c 107 l= _ + DATA ~ ~ DATA = _ MODEL MODEL 1o6 = ~ MIX/DIF 1o6 MIX/DIF ~ ~ 0~~ 10 _ ~ 10 I I I ~ 0 15 30 45 60 75 90 0 15 30 45 60 75 90 CORE DEPTH cm CORE DEPTH crn Figure 5g Figure 5h FIGURE S. Continued Summary of parameter estimates (by case): Figure Background sedi- desig- mentation rate nation (mg/cm /yr) % Effluent solids Diffusion Co- Mixing depos iced in grid efficient depth sector (cm /see) (cm) 5A 250 0.5 - - SB 750 0.5 5C 500 0.3 - - 5D 500 0.7 5E 500 0.5 10- - 5F 500 0.S 10-7 - 5G 500 0.5 10 8 4 cm 5H S00 0.5 10-8 8 cm NOTES: The percent effluent solids deposited in the grid sector containing station 6C was uncorrected for degradation of volatile solids. Surface mixing was omitted from cases designed to test model sensitivity to variation in the molecular diffusion coefficient.

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191 discharge has contributed significantly to the accumulation of solids on the bottom in the vicinity of the outfall. Based on the current discharge rate and effluent quality, estimates of volatile and refrac- tory solids fractions, etc., outfall-related solids now comprise about 9 percent of the total particulate flux to the bottom at station 6C. From the record of JWPCP solids emissions, it is apparent that this percentage was much higher prior to implementation of partial secondary treatment. Effluent-related contributions at more distant stations are much less significant. Model simulations indicate that the effect of pore diffusion on She distribution of DDT in Palos Verdes sediment is minimal. At D = 10- cm /see, molecular diffusion smooths the calculated profile without mitigating the steep (calculated) drop in DDT concentration near the surface. If the diffusion coefficient is reduced by an order of magnitude, its effect is negligible (Figure be). Increasing the diffusion coefficient by a factor of 10 (Figure 5f) results in a reasonable representation of near-surface DDT levels at station 6C but broadens the DDT peak and extends elevated concentrations to depths that are not supported by monitoring data. The estimated diffusion coefficient (D ~ 10- cm /see) represents an upper limit since values at and below that level are virtually indistinguishable. DDT profiles are better reproduced by creating a well-mixed zone of arbitrary dimensions among the surface sediments. The physical basis of such a zone lies in either frequent sediment resuspension (unlikely in light of the apparent depth of the mixing zone) or bioturbation. The estimated depth of such a well-mixed or biologically active zone at station 6C is 6 cm. The primary effect of increasing or decreasing the dimension of the mixing zone is evidenced in the estimated surface DDT concentration, which increases nearly an order of magnitude in response to variation in mixing-zone depth between 4 and 8 cm (Figure 5g and 5h). Sedimentation model (no mixing) results were included in Figure 5(e-h) to illustrate further the importance of mixing to accurate representation of surface sediment DDT concentrations. In Figure Se and Sf, surface mixing effects were eliminated in order to isolate the effect of order-of-magnitude-scale variation in diffusivity. Insight and Limitations Although the sedimentation/mixing model (1) is capable of repro- ducing sediment profiles of volatile solids and DDT concentrations, and (2) exhibits a satisfactory degree of sensitivity relative to selection of parameter estimates, it provides an incomplete mechanical framework within which to identify the primary determinants of DDT distribution. Nevertheless, we feel that the following mechanistic observations relative to model behavior are justified: 1. Physical rather than chemical processes will determine the long-term fate of DDT among sediments of the Palos Verdes

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192 shelf. Chemical factors of practical importance are that (1) DDT will not chemically or biochemically degrade within the foreseeable future and (2) surface affinity or hydrophobic effects ensure that DDT does not behave as a solute. . The primary physical determinants of DDT distribution along the 61-m depth contour are discrete particle sedimentation and sedi- ment mixing due to bioturbation. No attempt was made to ration- alize either process--natural and outfall-related sedimentation rates were developed via parameter fitting using sediment pro- files of volatile solids; bioturbation was simulated by creating a well-mixed zone of arbitrary depth among the surface sediments. 3. Natural sedimentation rapidly decreases with distance beyond the break of the Palos Verdes shelf. 4. There is little spatial variation in the background sedimenta- tion rate along the 61-m contour suggesting that (1) local variation within the shoreline erosion rate is not a primary determinant of sediment accumulation at that depth and (2) effluent-related solids are not responsible for appreciable flocculation of slow-settling natural particulates. I. The sedimentation/mixing model could not adequately reproduce the sediment profiles of volatile solids and DDT at the ED (Figure 1, 30-m depth) sampling location (data not shown). That site is characterized by unusually high surface concentrations of volatile solids and DDT. It is possible that in shallower waters processes not considered here, such as wave-driven sediment resuspension, are responsible for re-exposure of buried materials, including relatively high-level DDT concentrations. Extensions Results suggest that there is a great deal to gain from an approach to sediment modeling in which component physical, chemical, and biolog- ical processes are added sequentially to the overall model. Such an approach is especially useful when potentially important unit processes are complex--when existing data do not support a mechanistic treatment. The deposition of effluent-related solids on the Palos Verdes shelf has been successfully modeled by several investigators (Hendricks, 1978, 1982, 1984; Koh, 1982~. Comparison of LACED sediment core measurements with quality characteristics predicted on the basis of effluent quality data and sedimentation pattern predictions alone were used to assess the importance of processes (sediment resuspension, biological mixing) that are less amenable to mathematical modeling. The importance of surface-mixing processes as determinants of the ver- tical distribution of sediment DDT is clear from the exercise. Sedi- ment mixing was then treated empirically to reproduce sediment pro- files. From the latter analysis, it is apparent that periodic sediment resuspension is an important determinant of the vertical distribution of sediment contaminants at the shelf 3)-m depth contour. A similar approach might be applied to sediment modeling in any situation in

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193 which sediment quality data are more reliable or more easily obtained than the physical data necessary for construction of mechanistic models. In summary, rational treatment of the fate of sediment contaminants awaits development of an adequate base of physical oceanographic data. Shortcomings in this area, even among the most heavily studied coastal sediments in the country, were outlined in the text. Absent reliable theory or supporting data, empirical approaches based in sediment chem- istry can identify determinants of sediment quality and contaminant distribution. In cases where current-driven sediment resuspension can be neglected, such models permit prediction of sediment quality changes following perturbations in appropriate forcing functions. Improvements in existing theory and a greater commitment to collection of physical data are necessary to support rational model--when sediment resuspen- sion is an important determinant of sediment quality. In light of Marine Board instructions to consider engineering reme- dies for contaminated sediments, it is worthwhile considering the magni- tude of problems imposed by contaminants in place on the Palos Verdes shelf and the likelihood of finding engineered solutions to these prob- lems. On the bases of specific chemical and biological indicators of sediment quality, Palos Verdes sediments are among the most impacted in the nation. Dr. Zarba's work (this volume) on the severity of national sediment contamination has produced suggested contaminant levels for categorizing the severity of DOT and metals contamination in sediments. A significant portion of the shelf sediments fall among those most heavily contaminated in the nation using either metals or DDT criteria. Dr. Robertson's mussel tissue measurements of metals and pesticides (also in this volume), which were not designed to identify contaminant "hot spots" but to suggest portions of the country likely to contain a high level of general sediment contamination, found that animals exposed to Palos Verdes contaminants contained the highest levels of total DOT and cadmium encountered in his survey. Despite the apparent severity of chemical effects, economic impacts and human health effects of shelf contamination are modest or unproven. Nevertheless, these sediments would be granted high priority for - remedial activities should remediation measures prove economically feasible and cost effective. They will not. The areal extent of severely contaminated sediments (by Dr. Zarba's criteria and others) is on the order of 10 km (alongshore) by 4 km (cross - shore ~ . Contaminant removal would demand dredging to an average depth of about 25 cm over that region. Thus th7 total volume of sedi- ments to be removed would be on the order of 10 m . or a cube roughly 2.5 football fields in each dimension. Could these be removed, they would present a remarkable disposal problem. The feasi- bility of dredging from 30 to 150 m depth is itself uncertain. Dr. Herbich ~ this volume ~ indicated that modern dredge capabilities encom- pass removal of 2, 000 m /hr~ from a depth of 20 m. Even if this capacity could be extended to the depths of the contaminated sediments it would take seven months of continuous operation of the best equipment known to remove this material.

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194 To cap the same area wit) clean material to a depth of even 0.6 m would require a minimum 2x10 m of clean sediment, and the environmental problems associated with sediment resuspension during such an activity might be exceptionally severe. Engineered remediation strategies of a nature applicable in shallower waters in which contamination is more contained are inappropriate in this setting. SUMMARY AND CONCLUS IONS The primary physical determinants of the distribution of refrac- tile, nondiffusing chemicals among sediments of the Palos Verdes shelf 61-m depth contour include sedimentation of natural and outfall-related particles and bioturbation of surface sediments. Processes of secon- dary or perhaps negligible importance to the long-term fate of sediment DDT at that depth include sediment resuspension and diffusion through sediment pores. In shallower water, sediment resuspension may be an important factor. The background or natural sedimentation rate along the 61-m depth contour is approximately 500 dry mg/cm lyre Flocculation of natural particles due to the discharge of effluent-related solids is not apparent. The background sedimentation rate decreases rapidly beyond the shelf break. No matter what treatment scenario is selected for the JWPCP, the flux of natural particles to the bottom will gradually diminish the surface sediment concentration of DDT along the 61-m depth contour with attendant benefits for fish tissue concentrations of DDT and sediment infaunal ecology. However, the rate at which DDT will decrease at the surface is sensitive to the solids HER from the Whites Point outfall system. Implementation of full secondary treatment at JUPCP results in nearly a 7S percent increase in the predicted, year-2005 surface sedi- ment concentration of DDT at station 6C relative to a partial secondary treatment (or no-change) scenario. ACKNOWLEDGMENTS Funding for this research was provided by Los Angeles County Sanita- tion Districts. We thank Irwin Haydock and Jan Stull for general assis- tance and advice. The manuscript was prepared by Mrs. Sharon Solomon of the University of Arizona Civil Engineering staff. Portions of this work were presented at the Sediment Dynamics Workshop, October 19-21, California State Polytechnic University, Pomona, California. REFERENCES Cross, J. N. 1984. Tumors in fish collected on the Palos Verdes shelf . Southern California Coastal Water Research Proj ect Biennial Report, 1983-1 984, W. Bascom, ed. Long Beach, California: SCOURS.

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195 Gossett, R. W., H. W. Puffer, R. H. Arthur, J. F. Alfafara, and D. R. Young. 1982. Levels of trace organic compounds in sportfish from southern California. Southern California Coastal Water Research Project Biennial Report 1981-1982, W. Bascom, ed. Long Beach, California: SCCWRP. Gossett, R. U., H. W. Puffer, R. H. Arthur, and D. R. Young. 1983. DDT, PUB and benzo~a~pyrene levels in white croaker (Genyonemus lineatus) from Southern California. Mar. Poll. Bull. 14~29:60-65. Hendricks, T. J. 1988. Development of methods for estimating the changes in marine sediments as a result of the discharge of sewered municipal wastewaters through submarine outfalls : Part II , resuspen- s~on processes, draft copy. Final report for U.S. EPA. Hendricks, T. J. 1984. Predicting sediment quality around outfalls. Southern California Coastal Water Research Project Biennial Report 1983-1984' W. Bascom, ed. Long Beach, California: SCCWRP. Hendricks, T. J. 1982. An advanced sediment quality model. Southern California Coastal Water Research Project Biennial Report 1981-1983, U. Bascom, ed. Long Beach, California: SCCURP. Hendricks, T. J. 1978. Forecasting changes in sediments near outfalls. Southern California Coastal Water Research Proj ect Annual Report 1978, W. Bascom, ed. Long Beach, California: SCCWRP . Keith , J . O ., L. A. Woods , and E . G . Hunt . 1970 . Reproductive failure in brown pelicans on the Pacific coast. Trans. North Am. Wildl, Nat . Res our . Conf . pp . 56 - 6 ~ . Koh, R. C. V. 1982 . Initial sedimentation of waste particulates dis - charged from ocean outfalls. Environ. Sci. Technol. 16:757-763. Myers, E. P. 1974. The concentration and isotopic composition of carbon in marine sediments affected by a sewage discharge. Ph.D. Thesis. California Insti tute of Technology, Pasadena, California . Oshida, P. S. and J. L. Wright. 1976. Acute responses of marine inverte- brates to chromium. Southern California Coastal Water Research Proj ect Annual Report 1976 . E1 Segundo, California: SCCWRP . Risebraugh, R. W., O. B. Mengel, D. J. Martin and H. S. Olcott. 1967. DOT residues in Pacific seabirds: A persistent insecticide in marine food chains . Nature 216: 589 - 591. Risebraugh, R. W., F. C. Sibley, and M. N. Kirven. 1971. Reproductive failure of the brown pelican on Anacapa Island in 1969. Amer. Birds 25: 8 - 9. Sherwood, M. 1976 . Fin erosi on disease induced in the laboratory. Southern California Coastal Water Research Project Annual Report 1976. E1 Segundo, California: SCC~RP. Stull, J. K., C. I. Haydock, R. W. Smith, and D. E. Montagne. 1986. Long-term changes In the benthic community on the coastal shelf of Palos Verdes, Southern California. Mar. Biol. 91:539-551. Word, J. Q. 1978. The ~nfaunal trophtc index. Southern California Coastal Water Research Project Annual Report 1978, U. Bascom, ed. Long Beach, California: SCCWRP. Young, D. R., R. W. Gossett, and T. C. Heesen. 1988. Persistence of chlorinated hydrocarbon contamination in a California marine eco- system. In Urban Wastes in Coastal Marine Environments, Vol. 5, Oceanic Processes in Marine Pollution Series, D. Wolfe and T P. O'Connor, eds.

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196 APPENDIX MODELING APPROACH FOR SEDIMENTATION AND SEDIMENTATION/MIXING MODELS Computational procedures are summarized below: 1. The uncorrected flux of outfall-related solids to specific sediment locations, Suncorr (mg/cm -yr), is estimated as follows fraction of effluent Suncorr solids which reach (solids MER) ~ 1 the designated area LareaJ - [solids fractions SS x 105 MT x 103kg x 106 mg yr MT kg x 1 X {I l X I l 0.25 ~ 1 km2 103m J ~ lOOcm J Suncorr [ g ~ ~ (solids fractions) (SS) x 40,000 cm2-yr Notes: 1. The fraction of effluent solids reaching specific grid sectors or "solids fraction" was initially estimated from the modeling efforts of LACED personnel using Hendricks model for sediment deposition on the Palos Verdes shelf. Values were subsequently fitted to reproduce volatile solids profiles in sediment cores. 2. Grid-sector dimensions are 0.25 km x 1.0 km. 3. SS values, or suspended solids mass emission rates at JWPCP are taken from Figure 3. 2. Biological degradation of solids reduces the volatile solids content of discharged solids by the fraction fVSd in the water column prior to deposition. Thus, the total solids of sewage origin which reach a core site, Ssr (mg/cm2-yr) is: Ssr Suncorr (1 - fVS x fad) where fVS is the ratio of volatile solids to total solids in JWPCP effluent (estimated at 70 percent from LACED records ~ . 3. The flux of volatile solids of sewage origin to the sediment site is given by: VSsr (SUnCOrr) (fVS) (1 - fVSd)

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197 4. The total flux of solids to a site is the sum of the sewage- related solids and the background (or natural) sediment flux: Sflux Ssr + Snat Note: Snag was originally estimatesd from the depth of elevated DOT concentrations at the TIC monitoring site. Values were subsequently fitted to reproduce sediment volatile solids profiles. The volatile solids content of natural particulate material (fVSnat) was estimated at 7 percent (Hendricks, 1984~. The contribution of background sedimentation to the local flux of volatile solids is equal to Snat times f~Snat. That is: Reseat = Snat X f\JSnat 6. The average volatile solids content (VS in percent) of solids which reach the sediments is therefore: VS ~ VSsr + VSnat X 100 Sflux 7. The water content (M, in percent) and the sediment wet density (p in g/cm3) were estimated using the following empirical relationships: M ~ 1.15 VS ~ 26.238 p ~ -0.01673 VS + 1.7938 Note: Relationships shown were determined using LACSD sediment data and a linear regression algorithm. 8. The depth of sediment (DEPtot in cm) added during time intervals of 1 year is given by: DEPtot c Sflux . ~0~3 {1 - 0.01M) p 9. The diffusion of DDT within sediments was calculated using a one- dimensional forward explicit finite difference equation: ct ~x' ~ C (x) - DAt tC`x+ly ~ C(x-l) Ax2 - 2 C(x)]

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198 where C is the DDT concentration in the sediment [pg/kg], ct is the new concentration after a time interval At ~ 1 day, Ax ~ 2cm is the node spacing, with 40 nodes per sediment profile. No loss of DDT from sediments was assumed. 10. Mixing was incorporated by equally distributing DDT within the designated number of 2 cm sediment compartments over which mixin would occur. New sediment was incorporated into the mising mode only after 2 cm of new material had accumulated. NOTATION Influx VSnat AS M p DEPtot C D - ~x At ~1 solids flux (uncorrected from outfall (mg/cm2-yr) Mass emission rate (metric tons/yr) fraction of volatile solids that are biologically degraded fraction of total solids that are volatile volatile solids flux of sewage origin to sediment (mg/cm2-yr) solids flux of sewage origin to sediment (mg/cm2-yr) solids flux of natural origin to sediment (mg/cm2-yr) fraction of volatile solids of natural (non-sewage) origin in sedimenting material sum of sewage and natural (non-sewage) sediment solids (mg/cm2-yr) volatile solids flux of natural origin to sediment (mg/cm2-yr) percent of sediment solids that is volatile moisture, or percent water content of sediment sediment wet density (g/cm3) depth of sediment accumulation each year (cm) concentration of DDT in sediment (pg/kg) diffusivity (cm2/s) distance between nodes in finite difference model (cm) time integral in f inite difference model ~ d)