EXAMS model

A very significant advance was made by Baughman and Lassiter (5) when they suggested using evaluative environments for elucidation of the environmental behavior of chemicals. This led to the EXAMS model (6), the studies of selected chemicals by Smith et al (7, 8), the development of "Unit Worlds" by Neely and Mackay (9) and Mackay and Paterson (2), and the incorporation of similar Unit Worlds into hazard assessment by Schmidt-Bleek et al (10). 

This gives an example of fate modeling in which the risks of an insect growth inhibitor, CGA-72662, in aquatic environments were assessed using a combination of the SWRRB and EXAMS mathematical models.. Runoff of CGA-72662 from agricultural watersheds was estimated using the SWRRB model. The runoff data were then used to estimate the loading of CGA-72662 into the EXAMS model for aquatic environments. EXAMS was used to estimate the maximum concentrations of CGA-72662 that would occur in various compartments of the defined ponds and lakes. The maximum expected environmental concentrations of CGA-72662 in water were then compared with acute and chronic toxicity data for CGA-72662 in fish and aquatic invertebrates in order to establish a safety factor for CGA-72662 in aquatic environments. 

Any compartment of the aquatic ecosystem can be represented as a particular volume containing water, particulate matter, biota, dissolved materials, etc. Loadings and exports are represented as mass fluxes across the boundaries of the volume element (processes Se, D and L). Reactive processes are treated as point processes centered within the volume. Thus, the EXAMS model takes into account both physical and chemical processes that affect the environmental fate of a particular chemical. 

The automated EXAMS model consists of a set of FORTRAN programs which calculates the fate, exposure and dissipation of the chemical from input environmental data such as 1) Global parameters (rainfall, irradiance, latitude), 2) Biological parameters (biomass, bacterial counts, chlorophyll), 3) Depths and in-lows, 4) Sediment characteristics, 5) Wind, 6) Evaporation, 7) Aeration, 8) Advective and turbulent interconnections, 9) Water flow, 10) Sediment flow, 11) pH and pOH, and 12) Temperature. Also characteristics of the chemical are taken into account such as hydrolysis photolysis, oxidation, biolysis, and volatility. 

The following data were input into the EXAMS model to determine the fate of CGA-72662 resulting from runoff (0.001 lbs. ai/A) into ponds or lakes. 

Aquatic safety factors ranged from 5.5 X 107 for rainbow trout in ponds to 9.3 X 108 for daphnia in lakes. These data emphasize that exposure levels of CGA-72662 are low and must be taken into account for a risk assessment. Although the persistence of CGA-72662 in eutrophic lakes is relatively long, the exposure is extremely low and of no environmental consequence. Overall, use of SWRRB runoff and EXAMS models show CGA-72662 to be very safe in aquatic habitats when used on vegetables in Florida muck soil. 

The EXAMS model was designated for point source pollution examination. However, modification for non point source pollution can be done. 

Table VIII shows a sensitivity analysis on the EXAMS model. Changing the input load dramatically changes the concentration of chemical in both water and sediment. Photolysis rates appear to effect the model less than input loads. Changing the soil type effects the purification time of the system and not so much the water concentrations of the chemical indicating the influence of chemical adsorption to degradation.

Photolysis direct kp = 2 x 10 h (EXAMS model, Wolfe et al. 1980a) ... 

Table 8.4. Physicochemical and environmental fate properties of PBO used in EXAMS modelling...

These parameters were known or measurable for the chemicals studied. The EXAMS model was previously used successfully for modelling volatilization processes from waste ponds (28), a somewhat similar application. 

Figure 6 Illustrates pseudo-first-order system halflives, estimated by the EXAMS model ( 9), for photolysis of a series of generic organic substrates with differing K s (FaK ) and sedlment/water partition coefficients, (K ) out with the same photolysis rate constants in the water column of a freshwater pond. As the partition coefficients Increase, the fraction of substrate In the illuminated water column, and thus the system loss rate, decreases due to Increased sorption Into bottom sediments. It Is noteworthy that this simulation, when compared with Figure 5, Indicates that sorption Into bottom sediments has little or no effect on the total rate of photochemical loss for a preponderance of Industrial chemicals.

Figure 9.4 Risk assessment for an aquatic environment based on a probabilistic procedure into which the concept of varying sensitivity in multispecies communities is incorporated (Nendza, Volmer and Klein, 1990). Exposure and effects are determined separately from experimental or, if not available, QSAR data. Physico-chemical data and information on bioaccumulation and biotransformation are the input for computer simulations of transport and distribution processes that estimate the concentrations of a potential contaminant in a selected river scenario, using, for example, the EXAMS model (Bums, Cline and Lassiter, 1982). For the effects assessment, the log-normal sensitivity distribution is calculated from ecotoxicological data and the effective concentrations for the most sensitive species are determined. The exposure concentrations and toxicity data are then compared by analysis of variance to give a measure of risk for the environment. Modified from Nendza, Volmer and Klein (1990) with kind permission from Kluwer Academic Publishers, Dordrecht.

---