Faculty Publications and Presentations

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Book Chapter in Aquatic Toxicology and Environmental Fate: Ninth Volume, ASTM STP 921. T. M. Poston and R. Purdy, eds. American Society for Testing and Materials, Philadelphia, 1986, pp 192-206.


Environmental risk assessment performed for chemicals involves exposure assessment, effects assessment, and risk integration. The nature of living microorganisms (growth, replication. and survival), as compared to chemicals, requires that their biological attributes be integrated into risk assessment. Biological attributes have generally been dealt with in effects assessment and not exposure assessment models. Thus, exposure assessment models that characterize source, transport, transformation, and fate (effective environmental concentration, area, and duration of exposure) of genetically engineered microorganisms must incorporate biological factors along with physicochemical factors.

A study to assess the state of the art of exposure models for organisms and microorganisms in air, soil, and water was undertaken. Mathematical models developed during the past 15 years were organized into three categories: organism population dynamics, source features and transport, and management and control. One hundred forty-eight models were examined, and 56 were judged to have potential as exposure models. These 56 were screened to 31 models that were then evaluated against eight components that the ideal biotechnology model should have: (a) five state/process components (organism population, source application, exposure site, movement, and imposed management) and (b) three software components (user friendliness, availability/implementability, and flexibility). Each model was rated by individual components, combinations of two components, and total state/process components. An ideal exposure assessment model with high scores in all components was not found.

Combining two or more models so that the strong components of one compensate for the weak components of another was concluded to be the best approach for obtaining a predictive model for microorganisms. Potential couplings were ascertained from among the 31 models. Most of these couplings would combine an organism population dynamics model with a model from the U. S. Environmental Protection Agency's Graphical Exposure Modeling System (source and transport oriented models).