United States Environmental Protection Agency Environmental Research Laboratory Athens GA 30613 Research and Development EPA-600/S3-83-007 Apr. 1983 Project Summary Verification of a Toxic Organic Substance Transport and Bioaccumulation Model Jerald L Schnoor, Narasinga Rao, Kathryn J. Cartwright, Richard M. Noll, and Carlos E. Ruiz-Calzada A field verification of the Toxic Or- ganic Substance Transport and Bioac- cumulation Model (TOXIC) was con- ducted using the insecticide dieldrin and the herbicides alachlor and atrazine as the test compounds. The test sites were two Iowa reservoirs. The verifica- tion procedure included both steady- state analyses and quasi-dynamic simu- lations using time-variable flows and pollutant loadings along with model coefficients derived from laboratory and literature data. Laboratory measurements were ap- plied in simulations using alachlor, atrazine and dieldrin, and model predic- tions were well within an order-of- magnitude of field observations. For the herbicide, alachlor, for example, labora- tory protocol measurements were used directly in model simulations with ex- cellent agreement between model predictions and measured concentra- tions. The TOXIC model, therefore, was considered to be field verified. More- over, the successful field verification supports the validity of EPA's Exposure Analysis Modeling System (EXAMS), which handles pollutant transport and transformation kinetics in an almost identical manner. This Project Summary was developed by EPA's Environmental Research Labo- ratory, Athens, GA, to announce key findings of the research project that is fully documented in a separate report of the same title (see Project Report order- ing information at back). Introduction A number of mathematical models have been developed in recent years to assess the fate and transport of agricultural chemicals in the aquatic environment. Such models contain kinetic formulations that describe the chemical, physical and biological reactions that a pesticide can undergo once it reaches a water body. Chemical hydrolysis, volatilization, photol- ysis, and biological degradation comprise the reactions considered in these models. The relative importance of the various pathways of pesticide fate (hydrolysis, volatilization, photolysis, biological degra- dation, oxidation, and sorption) may be assessed in the laboratory in conjunction with field evaluations. These models generally have not com- bined fate and transport modeling with biological impacts such as bioconcentra- tion and, heretofore, have not been extensively verified by comparing model predictions with site-specific field meas- urements. In this research, the Toxic Organic Substances Transport and Bio- accumulation Model (TOXIC) was devel- oped and verified in an application on the Coralville and Rathbun Reservoirs in Iowa. The reader should realize that the kinetics handled by TOXIC are very similar to those in EPA's Exposure Analysis Modeling System (EXAMS). Therefore, many of the conclusions drawn from this study will be somewhat applicable to EXAMS as well. ------- Model Description A schematic of the kinetics and trans- port processes that comprise TOXIC, which is an extension of a model devel- oped by Stanford Research Institute (SRI), is shown in Figure 1. The solid lines in Figure 1 are in accordance with the original SRI model formulation. Modifica- tions in both the kinetics and transport algorithms made in the development of TOXIC and intended to add realism to the model are represented by dashed lines. A two-compartment or "pond" representa- tion of the test reservoir sites was initially assumed because there existed little in- reservoir data with which to calibrate a multi-compartment model. Figure 2 de- picts the physical configurations of the two-compartment pond model and a more complex eight-compartment lake model also utilized in the analysis. Coralville Reservoir dimensions were used in the pond configuration for model calibration, and simulations were later performed using the lake configuration as well. In addition to chemical and biological reaction pathways, uptake and depuration (excretion and metabolism) in fish were included in the model. The bioaccumula- tion model formulation is depicted in Figure 3. Biouptake was assumed to be proportional to the product of the fish biomass and the dissolved pesticide con- centration. Pesticide was assumed to be removed by the fish as water passed the gill membrane. Biouptake from sediment and/or food (prey) was also included in this portion of the model. For the applica- tion portion of this study, it was assumed that the pesticide residue was metabo- lized within the fish, but in some cases it might be necessary to recycle the depu- rated pesticide as a separate dissolved input, as shown in Figure 3. Field Validation Tests with Dieldrin in Coralville Reservoir Agricultural use of pesticides is wide- spread in Iowa, particularly the grass and broadleaf herbicides and row crop soil insecticides. One insecticide widely used from 1960 to 1975 to control the corn rootworm and cutworm was the chlori- nated hydrocarbon, aldrin, which metab- olizes to a persistent epoxide, dieldrin. Both a two-compartment pond and multi- compartment lake version of TOXIC were applied to the Coralville Reservoir to test the ability of the model to predict the fate and effects of dieldrin in the ecosystem. Although the historical field data avail- able reflected individual storm events. SKI Model Modifications , Wetfa/l Dryfall Absorption Volatilization ' 1 r\irt*t** f- 'v-—» U^^ 6 * t ' / \ i_) Microlayer Formation? Photolysis Photolysis Dissolved Pesticide /sis 1 Biolysis i 1 Adsorption Desorntinn Paniculate Pesticide Biouptake j i Hydrolysis j Biolysis Sed T Diffusion Biota Death and Excretion Biouptake Scour Dissolved Hydrolysis Biolysis (Anaerobic) Paniculate Hydrolysis Biolysis (Anaerobic) Figure 1. Chemical kinetics and transport processes modeled in TOXIC. the goal here was to represent annual average concentrations and mass flows. Therefore, constant annual average in- flow and outflow rates were assumed, together with an average annual volume for the reservoir. Coralville Reservoir does not thermally stratify to any great extent, so the failure to include a hypolimnion compartment in the pond configuration of TOXIC was not viewed as a serious problem. The first test exercise used the two- compartment configuration of TOXIC. Because the objective of this simulation was to analyze annual average concen- trations, transport properties (i.e., flow, volume, and sedimentation rate) were averaged over the period of simulation. ------- The model simulation results versus the field data are shown in Figure 4. Dieldrin concentrations in water, shown in Figure 4, represent monthly grab sample field measurements. The peak concentrations during the runoff events recorded in the field data were not matched by the model results, since average inflow and a smooth loading rate function were as- sumed. Figure 4 also shows the model results and field data for dieldrin residues in sediment and the edible tissue of bottom feeding fish in Coralville Reservoir. A sensitivity analysis was performed to assess the importance of the partition coefficient. The results indicated that a several-fold increase or decrease of the partition coefficient from 0.5 to 2.0 to 0.10 changed the total concentration by approximately minus and plus 50%, re- spectively. Results also indicated that the bioconcentration of hydrophobic pesti- cides such as dieldrin in Coralville Reser- voir fish was directly proportional to the oil or lip'td content of the catch. Although the data were sparse, it appeared that such a simple bioconcentration model has validity. The model predictions estimated that 40% of the dieldrin inflow to Coralville Reservoir was lost through sedimentation and 50% was released through the dam gates of this relatively short detention- time reservoir. Uptake by fish accounted for the remaining 10% of the dieldrin input due to the extremely large fish biomass (1000 Ib/acre). The partitioning of dieldrin in the water column was 64% in the fish, 24% dissolved in the water, a nd less than 12% adsorbed to suspended solids. Mean residue levels in the edible tissue of bottom feeding fish eventually declined below the FDA guideline of 300 Aig/kg. Fish and sediment concentrations were found to be essentially in equilib- rium with the mean dissolved dieldrin concentrations. Under low flow condi- tions, the sediment became a net source for pesticide in the reservoir through desorption and pore water diffusion. Bottom feeding fish bioaccumulated dieldrin in proportion to the oil content (determined by petroleum ether extrac- tion) of the fish sample. Therefore, pollu- tant averages or composites for very oily fish tended to be higher than model predictions. Model projections indicated that by 1986, dieldrin residues in bottom feeding fish flesh should steadily decline to an average of less than 100 /^g/kg. To investigate the sensitivity of the model to compartmentization, an eight- — -| 0.3m —» 5000m K- 2 -Compartment Pond 1— t E CM 10 [• — 7800m — • / 2 / t 1 5 / 1 /J 8-Compartment Li p — 7800m — / 3 /t A 6 ft lAe Outflow o \ \ \ \ Water Compartment Sediment Compartment Figure 2. Physical configurations of the TOXIC model. Input Input Food Items Rapid Sorptive Equilibrium Sediment Fish Worms Metabolites Sedimentation y Hydrolysis Biolysis Photolysis Volatilization Oxidation Figure 3. Bioaccumulation model schematic. ------- L I I! 0.06 0.05 0.04 0.03 0.02 0.01 0.0 12 10 a 6 4 2 0 1500 1250 1000 750 500 250 Coralville Outflow 68 * €9 "70^ 71 ^72^ 73 ' 74 ' 75 r 76 T 77 T 78 ^ 79 Sediment Compartment Z Field data, X±1s 71 Model Results ' 65 ^70 ^77 ' 72 ^73 ' 74 ' 75 T 75 ' 77 ' 78 * 79 Bottom Feeding Fish Bioconcentration Factor BCF= 70,000 FDA Action Level Figure 4. 68 J 69 ' 70 ' 71 ' 72 ' 73 ' 74 r 75 ' 76 ' 77 ' 78 ' 79 ' /ear /Ve/ etef a a/jd model results for dieldrin in Coralville Reservoir. Numbers adjacent to the vertical bar represent the number of data points, and percentages are the percent oil or lipid content of the catch. compartment version of TOXIC was also applied to the Coralville. Even though field data were not available for each compartment, there appeared to be good agreement between model results and field observations. The addition of com- partments to the model provided insight into the dynamics of dieldrin transport, scour, and deposition. The only significant difference between execution of the two- compartment and the eight-compartment model was that a small amount of scour was introduced into the sediment com- partment of the eight-compartment ver- sion, resulting in a lower net sedimenta- tion rate. The resulting sediment residue levels from the two-compartment model were low by a factor of 2-4 compared to those of the eight-compartment model. This parameter was shown to be particularly sensitive to estimated rates, of degrada- tion of sorbed toxics. A more complex 25-compartment model was also applied to the reservoir using different estimates of sediment degradation and inflow concentrations. This quasi-dynamic modeling application used (1) steady, annual average flow (from daily measurements) for long-term simulations; (2) steady, annual average, flow-weighted solids (from daily suspend- ed solids measurements); and (3) time- variable toxicant loadings (influent con- centration). These results comprised the best estimate of what had actually taken place in the Coralville Reservoir on a mass flux basis over time. There are diminishing returns to simulations with greater and greater mechanistic realism and complexity, however. In this case, the 25-compartment simulation did not pro- vide significant additional insight about impacts on fish or flush-out rates as compared to the simpler model runs. It was further concluded that only where highly accurate information or informa- tion relative to acute effects is needed for a management decision will the use of a model with time.variable inputs be rou- tinely warranted. Specific analyses were also conducted concerning biomagnification and bioec- cumulation. The analyses showed that biomagnification is apparently not a sig- nificant problem, because bottom-feeding fish have the highest biomass and residue levels. The kinetics of bioaccumulation were also evaluated using an equation that accounted for uptake of dissolved toxic organics through: the gill, released from bed sediments, and ingestion offish prey, worms and benthic organisms. For ex- ample, the simulated dieldrin residues in game fish for the Coralville Reservoir are shown in Figure 5. More than 50% of uptake for all fish was estimated to be through the gills, but the next greatest input for game fish was from prey in- gestion. Based upon the kinetic analysis, the concentrations in fish appeared to be in or near equilibrium with the Coralville water and would be expected to respond rapidly to changes of dieldrin concentra- tions in water. A Dynamic Simulation Model for Alachlor and Atrazine: Field Validation Using Microcosm and Laboratory Studies The TOXIC model was further tested and validated using two soluble herbi- cides, alachlor and atrazine. A field validation was undertaken, and micro- cosm and laboratory studies were used to supplement the field data collected under spring runoff (or time-variable) conditions. A major objective of this research was to determine the feasibility of using labora- ------- 220 200- 180 - 160 140 - Aquatic Exposure Model Game Fish Food Items /f, = 0.0135/day = 0.0415/day I 1} ti r Gill+Sediment+Predation+Benthos successful field verification of TOXIC also supports the use of EPA's Exposure Analysis Modeling System (EXAMS), which incorporates similar modeling pro- cedures. As an example of the model's utility, the Iowa Conservation Commis- sion based its decision to lift its ban on commercial fishing in Coralville Reservoir in 1979 largely on a series of TOXIC simulations. 1968 70 72 74 76 78 80 82 84 86 Time (years) Figure S. Simulated dieldrin residues in Coralville Reservoir game fish. tory-derived rate constants directly in a field verification effort. The relatively soluble, biodegradable chemicals were chosen to complement the dieldri n study. The resulting modeling efforts on Lake Rathbun for the highly soluble herbicides alachlor and atrazine were much different than for hydrophobic pollutants such as dieldrin, which tend to sorb on sediment. In order to assess herbicide dynamics, a three-step effort was undertaken includ- ing biotransformation tests in natural waters, microcosm testing, and field data collection. In summary, the laboratory biotrans- formation and microcosm studies were helpful in predicting the dynamics of alachlor and atrazine in Lake Rathbun. Model predictions were within a factor of five for atrazine, a factor .of two for dieldrin, and a factor of one for alachlor. For most purposes, these would be accep- table simulations and the model should be considered as field verified. In these simulations, rate constants were not adjusted to fit the field data, that is, there was no model tuning. Laboratory and literature rate constants were used di- rectly in a comparison with field obser- vations. Conclusions The field verification exercise demon- strated the acceptable use of laboratory process rate measurements in a modeling study. Laboratory measurements were used in simulations of alachlor, atrazine, and dieldrin, and model predictions were well within an order-of-magnitude (maxi- mum of a factor of five) of field data. The ------- Jerald L Schnoor, Narasinga Rao, Kathryn J. Cartwright, Richard M. Noll, and Carlos E. Ruiz-Calzada are with the University of Iowa, Iowa City, I A 52242. T. O. Barnwell is the EPA Project Officer (see below). The complete report, entitled "Verification of a Toxic Organic Substance Trans- port andBioaccumulation Model." (Order No. PB 83-170 563; Cost: $17.50, subject to change) will be available only from: National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 Telephone: 703-487-4650 The EPA Project Officer can be contacted at: Environmental Research Laboratory U.S. Environmental Protection Agency College Station Road Athens, GA 30613 •&U. S. 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