Predicting the Fate of Persistent Organic Pollutants

PREDICTING THE FATE OF PERSISTENT ORGANIC POLLUTANTS

USING A BIOGEOCHEMICAL MODEL: Solutions

Created by

Susan Libes, Professor

Marine Science Department

Coastal Carolina University

Conway, South Carolina

For her Environmental Chemistry class after attending the 1996 NSF/DUE/UFE-sponsored

Summer Practicum on Environmental Problem Solving hosted by the New York Great Lakes Research Consortium

Background

There are many valuable research and management uses for a mass balance-based model of the fate and transport of toxic chemicals in aquatic systems. Most of these uses depend on the ability of the model to deterministically and quantitatively relate the concentrations of toxic compounds in water, sediments and biota to the source inputs. This type of model can then be used to predict the responses of a particular aquatic system to various alternative regulatory and remedial action scenarios. The LAKE TOX spreadsheet model can be used to compare the steady-state responses of a lake to a toxic chemical under many scenarios. This model includes many important biogeochemical processes, e.g., gaseous transport across the air-water interface, scavenging by particles, pelagic sedimentation of these particles, bioturbation, first-order degradation reactions, and uptake by aquatic organisms. The model makes an excellent tool for investigating the sensitivity of toxic chemical concentrations in the water column and active sediments to the various environmental conditions and processes that govern the fate and transport of toxic chemicals in large lakes, like the Great Lakes, which are similar to marine systems. This model was developed for the Great Lakes because of the long-standing and numerous pollution problems that these large systems suffer. The model could theoretically be applied to the oceans if we had a better understanding of how to model water circulation.

If you are interested in seeing the mathematics behind the modeling in this exercise, refer to the documents by T.C. Young and J.V. DePinto in your workshop notebook and CD.

Project

The object of this exercise is to evaluate how a large lake’s morphometric, hydraulic and sedimentary characteristics affect its response to loading of a hydrophobic organic chemical. We will examine PCBs that are persistent bioaccumulative toxins (PBT) and hormonally active agents (HAA). Loading is simulated as either an areal (watershed, non-point source) or atmospheric input or as a point-source input such as from a tributary or outfall pipe. Your task is to use the model to make the runs listed below for each of the Great Lakes: Superior, Erie, Michigan and Ontario. Table 1 gives a comparison of the morphometric and hydrologic properties of each lake. Table 2 gives the data needed to define the solids dynamics of each lake that includes the sediments as well as sinking and suspended particles. In addition to these lake-specific data, there are several additional model parameters (mostly chemical specific data) that we shall assume are the same for all four lakes. They are given in Table 3. All of these data have already been typed into each lake’s spreadsheet model so you have one spreadsheet file for each Great Lake. Before you start modeling, open all of the spreadsheets (ONTARTOX, SUPERTOX, ERIETOX and MICHTOX) and acclimate yourself to the model by answering the following questions. Copies of the spreadsheets are on the CD provided by the instructor.

1. For any one of the lakes, look at the worksheet entitled “LakeTOX Mass Bal” to answer the following questions.

What are the input pathways of PCBs to the lake?

ATMOSPHERIC DEPOSITION, GAS PHASE ABSORPTION, TRIBUTARY/POINT SOURCE LOADING

What are the output pathways from the lake?

VOLATILIZATION, OUTFLOW, WATER COLUMN DECAY, SEDIMENT DECAY, BURIAL

Is the difference between inputs and outputs significant, i.e., is the lake in steady state?

LAKE ~ STEADY STATE; ONLY 1-2 % DIFFERENCE BETWEEN INPUTS, OUTPUTS

2. Look at the worksheet entitled “WC and Sed Results” to answer the following questions:

In what two species/forms in the water column are PCBs found? DISSOLVED, PARTICULATE

In what two species/forms in the sediments are PCBs found? DISSOLVED, PARTICULATE

3. The model computes the concentrations of the species/forms using a competitive complexing approach (speciation). In this application, the equilibrium constants are referred to as “partition coefficients”. For any one of the lakes, look at the worksheet entitled “Input Data” to answer the following questions.

In the section labeled “PARTITIONING DATA”, find the two following parameters and record their original values (CHECK THAT THESE NUMBERS ARE THE SAME AS THOSE IN TABLES 1 – 3):

Org Carbon Partition Coefficient in the water column (Kocw): 1 X 106

Org Carbon Partition Coefficient in Sediments (Kocs): 1 X 105

Kocw = Concentration of toxicant in particles/Concentration of toxicant in water

Kocs = Concentration of toxicant in sediment/Concentration of toxicant in pore water

In the section entitled “CHEMICAL PROPERTIES AND DYNAMICS DATA”, find and record the value of the Decay rate of "dissolved" chemical in the water column: 0

What is the value of the Decay rate of "dissolved" chemical in Sediments? 0

What does this tell you about the relative reactivity of PCBs? VERY NON-REACTIVE

Under the section entitled “SOLIDS DYNAMICS ”, find and record in the following table the concentrations of the Suspended Solids in the water column for each lake.

Lake / Suspended Solids in Water Column (g/m3)
Superior / 0.5
Michigan / 1.0
Ontario / 0.65
Erie / 5.7

4. The model also computes the concentration of a toxicant in the tissues of organisms from each level of a four-level food chain. This calculation is done on the worksheet entitled: “Bioaccum”.

What are the four trophic levels in the model food chain?

PHYTOPLANKTON, ZOOPLANKTON, SMALL FISH, LARGE FISH

This bioaccumulation calculation also relies on a mass-balance approach. The following input processes are included. Adsorption of the pollutant from the water to organisms is modeled using a partition coefficient called a Bioconcentration Factor (BCF). This is defined as the toxicant concentration in the organism/toxicant concentration in the water. The other input, is through consumption of food contaminated with the toxicant. The latter is only a concern for consumers and not for primary producers.

Since the concentration of toxicant in a consumer is a complicated function of multiple input and output routes (e.g., surface absorption, food intake, depuration, excretion), the bioconcentration factors for these organisms are referred to as Bioaccumulation Factors (BAF) and represent the impact of all the processes taken together. (In the case of the phytoplankton the BCF is the BAF.) Loss of the toxicant through excretion is output process included in the model.

Because the concentration of a toxicant also depends on the mass of the organism, the model also must include corrections for changes due to growth (e.g., pollutant concentrations are “diluted” as fish grow, concentrated as they accumulate fat, etc.). Submodels for fish bioenergetics are used to estimate fish growth and can be found in the worksheets entitled: “smfish growth” and “lrgfish growth”. We do not have time to explore the bioenergetics model in this exercise.

Look at the graph at the bottom of the “Bioaccum” spreadsheet. What happens to the toxicant concentration with increasing trophic level?

THE TOXICANT CONCENTRATION INCREASES WITH INCREASING TROPHIC LEVEL

This is referred to as biomagnification. The degree of biomagnification (BMF) for each trophic step is computed by taking the ratio of the BAF’s for each of the two steps. For Lake Ontario:

What is the BMF for Phytoplankton-to-Zooplankton? 3.89

What is the BMF for Zooplankton-to-Small Fish? 3.19

What is the BMF for the Small Fish-to-Large Fish? 1.38

Give a possible explanation for why biomagnification occurs and why it varies from trophic level to trophic level.

TOXICANTS ARE PASSED UP THE FOOD CHAIN BECAUSE THEY ARE PREFERENTIALLY RETAINED IN TISSUES RATHER THAN DEGRADED OR EXCRETED. OR, METABOLISM VARIES AMONG TROPHIC LEVELS

If a toxicant is reactive, will it have as significant a biomagnification effect? Explain your answer.

NO, IT WILL BE DEGRADED IN THE ENVIRONMENT OR DETOXIFIED IN ORGANISMS BEFORE IT CAN BE PASSED UP THE FOOD CHAIN.

Model Run 1: Exploring the Effect of Equal Areal Loadings (Unequal Total Loadings)

1. Run the model for each lake using an equal areal loading (relative to the lake surface area) of 20 g/m2-yr of PCBs. To do this, remove any tributary and point source loading (make this value = 0) and adjust the atmospheric deposition until the areal atmospheric loading is 20 g/m2-yr (a rough dimensional analysis computation should help you estimate the appropriate value to enter). On a physical level, it is easiest to achieve a constant areal loading of pollutant from lake to lake using aerial deposition as the dry or wet fallout would have the same pollutant content from lake to lake. Record the resulting Total Chemical Loading in kg/yr for each lake in the following table. This value represents the sum of the delivery routes of pollutant: (1) river and point source loading (now set to 0), (2) atmospheric dry and wet fallout, and (3) gas phase adsorption (simple dissolution).

Lake / Total Loading (kg/yr)
Superior / 1,680
Michigan / 1,174
Ontario / 390
Erie / 506

FOR EACH CHART THAT FOLLOWS, BE SURE TO INCLUDE THE CHART AND THE DATA USED TO CONSTRUCT IT IN YOUR REPORT. INCLUDE A DESCRIPTIVE TITLE AND LABEL THE AXES (INCLUDING UNITS).

1. Make a bar chart (as illustrated below) comparing the steady-state water column concentrations of the particulate (ng/g) and dissolved (ng/L) species among the lakes.

1. Make a similar chart comparing the total sediment concentrations (ng/g) for each lake.

Which lake(s) has the highest steady-state concentration in each medium (water and sediment)?

Water: SUPERIOR, MICHIGAN Sediment: ERIE

Which lake(s) has the lowest?

Water: ONTARIO Sediment: SUPERIOR, MICHIGAN

Explain why the lakes have different responses to the same loading. Hint: Look at the differences in properties given in Tables 1 and 2.

Water: SUPERIOR AND MICHIGAN HAVE MUCH LONGER HYDRAULIC RETENTION TIMES AND THE LOWEST SUSPENDED SOLIDS
Sediment: ERIE HAS THE HIGHEST PARTICLE CONCENTRATIONS AND SEDIMENTATION RATES.

4. Make a bar chart showing bioaccumulation across the four trophic levels for each lake as shown above.

Explain the general trends seen in the bioaccumulation chart within and between lakes.

SUPERIOR AND MICHIGAN HAVE HIGHER BIOACCUMULATION AT ALL TROPHIC LEVELS BECAUSE THEY HAVE HIGHER WATER COLUMN [PCB] BIOMAGNIFICATION IS DRAMATIC IN THE FOOD CHAIN

Model Run 2: Exploring the Effect of Equal Total Loading

1. Repeat Run #1 using a constant total PCB loading of 5000 kg/y. This loading models the effects of point source inputs through either tributaries or outfall pipes. To do this, zero out the Atmospheric Deposition, and enter 5000 kg/yr as the Tributary and Point Source Loading. Make a bar chart comparing the steady-state water column concentration for each lake at this new loading level.

1. Make a similar plot comparing the sediment concentration for each lake.

1. Also make a bar chart showing bioaccumulation across the four trophic levels for each lake.

1. Compare the results of Run #2 to Run #1 by answering the following questions. Hint: Make sure to compare the relative size of the loadings between Runs 1 and 2 using common units.

What effect does this change in loading have on the water and sediment concentrations? Explain why this occurs.

ALL CONCENTRATIONS RISE BECAUSE LOADING IS HIGHER IN ALL LAKES (~3X HIGHER IN SUPERIOR TO ~13X HIGHER IN ONTARIO)

Is the order of response among the lakes the same? If so, why? If not, why not?

NO. ONTARIO AND ERIE NOW HAVE THE HIGHEST CONCENTRATIONS BECAUSE THE TOTAL LOADING IS THE SAME FOR ALL LAKES. BECAUSE ERIE HAS THE SMALLEST VOLUME, IT HAS THE HIGHEST [PCB].

How does this change in loading affect the bioaccumulation trends within each lake and between lakes?

IN RUN #1, EQUAL AREAL LOADING PRODUCED ROUGHLY EQUAL WATER COLUMN [PCB]s AND ROUGHLY EQUAL CONCENTRATIONS IN ORGANISM TISSUES AT ALL TROPHIC LEVELS. IN RUN #2, LAKES ONTARIO AND ERIE HAVE THE HIGHEST CONCENTRATIONS IN TISSUES AT ALL TROPHIC LEVELS BECAUSE THEY HAVE THE HIGHEST [PCB]s IN THEIR WATER COLUMNS WHERE ORGANISMS ARE EXPOSED.

Model Run 3: Exploring the Effects of Pollutant Type

1. Using the input data from Run #1 for Lake Erie, change Kocw = 105 to 106 and Kocs = 104 to 105 (increased hydrophobicity) and then change Kocw to 104 and Kocs to 103 (decreased hydrophobicity). Since a given toxicant has a unique Kocw and Kocs, changing these parameters gives you a chance to see what the behavior of different toxicants would be like. The higher the Koc, the more hydrophobic the chemical and hence the less soluble in water it is. Plot the total water column response for all three runs on a bar chart.
2. Make a similar plot comparing the total sediment concentrations for each run.
3. Make a bar chart showing bioaccumulation across the four trophic levels for Lake Erie as shown below.

Explain what happens to the partitioning of the toxicant between sediment and water as the hydrophobicity of the toxicant is increased. Explain why this happens.

AS HYDROPHOBICITY INCREASES, THE PCBs ARE LESS WATER SOLUBLE AND PARTITION MORE STRONGLY INTO THE SEDIMENTS

Which chemicals (the most or the least hydrophobic) create the biggest sediment pollution problems? Why?

THE MOST HYDROPHOBIC. THEY ARE STRONGLY ATTRACTED TO THE ORGANIC FRACTION OF SEDIMENTS

Explain what should happen to the bioaccumulation of toxicants as the hydrophobicity of the toxicant is increased. Did you observe this? If not, explain what needs to be changed in the model to produce more realistic bioaccumulation results.

BIOACCUMULATION SHOULD INCREASE AS WATER SOLUBILITY DECREASES. THE MODEL DOES NOT REFLECT THIS BECAUSE THE BCFs AND BAFs IN THE BIOACCUMULATION MODEL HAVE NOT BEEN CHANGED

If you have time remaining, feel free to explore the sensitivity of the model for one lake to changes in one input or loading parameter at a time. Try +2X and +10X changes. BE SURE TO SAVE THE FILES UNDER NEW NAMES BEFORE MAKING CHANGES.

REFERENCES

DePinto, J.V. 1996. Spreadsheet model for PCB mass balance in the Great Lakes. Great Lakes Research Consortium Summer Practicum for Environmental Problem Solving. NSF/DUE/UFE.

Rodgers, P.W., J.V. DePinto, W. Booty and T. Slawecki. 1987. LTI toxics model application: PCB’s in lake Ontario – An exploratory application. Report to the IJC Task Force on Chemical Loadings. 49 p.

Stewart, D.J. 1996. Spreadsheet model for fish bioenergetics. Great Lakes Research Consortium Summer Practicum for Environmental Problem Solving. NSF/DUE/UFE.

Task Force on Chemical Loadings. 1988. Report on Modeling the Loading-Concentration Relationship for Critical Pollutants in the Great Lakes. Report to the Great Lakes Water Quality Board, International Joint Commission, Windsor, ON. 275 p.

Young, T.C. 1996. Spreadsheet model for bioaccumulation in an aquatic food chain. Great Lakes Research Consortium Summer Practicum for Environmental Problem Solving. NSF/DUE/UFE.

**This exercise was modified by J.M. Haynes (8/02). Dr. Libes’ exercise (1997) was derived from the GLRC/NSF Summer Practicum exercise created by J.V. DePinto (1996).**

Table 1. Comparison of Lake Morphometric and Hydrologic Properties

Property / Lake
Superior / Michigan / Ontario / Erie
Volume, V (m3) / 1.10 x 1013 / 4.72 x 1012 / 1.67 x 1012 / 4.90 x 1011
Surface Area, SA (m2) (V/z) / 8.30 x 1010 / 5.78 x 1010 / 1.95 x 1010 / 2.50 x 1010
Mean depth, z (m) / 132.5 / 81.7 / 85.6 / 19.6
SA/V Ratio (m-1) / 0.0075 / 0.012 / 0.012 / 0.051
Hydraulic Outflow, Q (m3/yr) / 6.40 x 1010 / 4.64 x 1010 / 2.00 x 1011 / 1.80 x 1011
Hydraulic Retention Time, Tw (yr)
(residence time of water) (V/Q) / 171.9 / 101.7 / 8.4 / 2.7
Overflow Rate, z/Tw (m/yr) / 0.77 / 0.80 / 10.26 / 7.20

Table 2. Comparison of Lake Solids Dynamics

Property / Lake
Superior / Michigan / Ontario / Erie
Water Column Suspended Solids, Sw (g/m3) / 0.5 / 1.0 / 0.65 / 5.7
Sediment Bulk Density, Ss (g/m3)
(particle density x porosity) / 2.40 x 105 / 2.40 x 105 / 2.40 x 105 / 2.40 x 105
Gross Water Column Settling Velocity, vs (m/yr) (for suspended solids from sediment trap data) / 500 / 500 / 500 / 500
Gross Resuspension Velocity, vr (m/yr) / 6.32 x 10-4 / 1.70 x 10-3 / 5.54 x 10-4 / 4.72 x 10-3
Sediment Burial Velocity, vb (m/yr) / 4.10 x 10-4 / 3.83 x 10-4 / 8.00 x 10-4 / 7.20 x 10-3
Net Water column Solids Deposition Rate, vn (m/yr) / 197 / 92 / 295 / 302
Net Water Column Deposition Flux, Fn (g/m2-yr) / 98.4 / 90.4 / 192.0 / 1721.5
Depth of upper mixed sediment layer, zs (m) (depth of bioturbated layer) / 0.05 / 0.05 / 0.05 / 0.05
Solids Residence Time in Sediments, Tss (yr) / 122 / 133 / 62.5 / 7.0
Solids Residence Time in Water Column, Tsw (yr) / 0.67 / .09 / 0.29 / 0.065

Table 3. Input Data Parameters Common to all Lakes

Property/Parameter / Value / Units
Gas film transfer rate, Ka / 1.58 x 105 / m/yr
Sediment-water diffusion rate, Kf / 3.65 / m/yr
Water column decay rate**, Kdw / 0 / yr-1
Sediment decay rate**, Kds / 0 / yr-1
Arochlor 1254 PCB molecular weight, Mw / 3.26 x 1011 / ng/mole
*Organic carbon partition coeff. (water), Kocw / 1 x 105 / L/kg
*Organic carbon partition coeff. (seds), Kocs / 1 x 104 / L/kg
Organic carbon fraction of SW, fOCW / 0.1
Organic carbon fraction of SS, fOCS / 0.04
Atmospheric PCB gas phase conc., Ca / 0.5 / ng/m3
Surface water temperature, T / 12 / oC

**first-order process for all chemical and biological degradation processes

*These partition coefficients are essentially equilibrium constants defined as:

Kocw = Concentration of toxicant in particles/Concentration of toxicant in water

Kocs = Concentration of toxicant in sediment/Concentration of toxicant in pore water

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