Input data EXAMS

EXAMS (Exposure alysis Modeling stem) is an elaborate computer program that predicts the fate of organic chemicals in aquatic systems (24). Most input data can be easily measured, calculated, or obtained from literature sources. For this reason, the program is readily accessible to chemists for use as a predictive tool. 

In the present study, EXAMS was used to calculate volatilization rate constants from water, wet soil, and a water-soil mixture. EXAMS uses the two-film theory to calculate volatilization rates from the 10 cm wind speed as discussed above. EXAMS requires as a minimum environment at least one littoral (water) and one benthic (sediment) compartment. A very small benthic compartment for the water system and a very small littoral compartment for the wet soil system (7.09 x 10 m3 volume and 1 x 10 8 m depth in both cases) was used, so that these compartments and their input parameters had a negligible effect on the calculated rates. For the water-soil system, the same proportions were used as in the laboratory experiment. Transfer rates between soil and water were assumed to be rapid relative to volatilization rates, and were set as recommended in the EXAMS manual (24). The input data needed by EXAMS in order to calculate volatilization rates from a water-soil system, using parathlon as an example, are shown in Table IV. 

Table IV. EXAMS Volatilization Rate Constant Calculation for a Water-Soil System Input Data for Parathlon ...

The differences in the calculated phenol concentrations in each of the rivers based on either QSAR or experimental data are negligible, which reflects the good agreement between the two sets of input data. Additionally, the features of EXAMS, which strongly depend on the assumed hydrological properties (e.g. flow rate and discharge, and river geometry), may contribute to the similarity of the results. The substantial differences between the two... 

In the course taught by the author, exams (including most of the final exam) are of the take-home variety. It is not practical to give a timed, in-class exam when numerical methods and using a computer are involved. In order to encourage individual work, each student is given a unique set of input data so that no two students... 

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. 

Table IX is a summary of the sensitivity of SWRRB and EXAMS to change in inputs. These data are taken from Tables VII and VIII. It can readily be seen that SWRRB is sensitive to rainfall intensity while EXAMS is sensitive to input load changes.

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.

Real-life data that is interesting is not as trivial as the example above. But much data does exist that can be split into a set of independent variables (the inputs to an ANN) and a set of dependent variables (the desired outputs of an ANN). Suppose you have a data set with five independent variables and one dependent variable, and you know through some combination of experiment and computation the values of all six variables for, say, 50 cases. [In our exam-... 

Assessment of mini-projects provide, useful student, course and curriculum assessment data, which are used as inputs for continuous curriculum improvement. There are several ways of carrying out course assessments like teacher/course evaluations, homework and test results, and minor, major exams. These methods do not provide any platform for assessing student s capability to integrate his learning in different courses... 

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