Quantification of aquatic environmental impact of electric power generation

Abstract

This project proposes a method for creating, to the extent of their predictability, the proper and timely forecasts of the aquatic ecosystem consequences of electric power system operation. A procedure is developed and intended for use in quantifying the ecological sacrifices associated with a number of desirable regional dispatch schedules. With the use of this technique, associated with a given reliability level, optimum scheduling schemes can be used to evaluate optimum dollar cost - environmental impact pairings. A prerequisite of the model was that it be flexible enough for use in the evaluation of aquasystem impacts from either existing or hypothesized systems, that is, that it could be used either as an operational tool or as a simulation tool. Specifically demonstrated is the feasibility of the quantification of various ecological impacts and its usefulness in effecting compatibility between the power generating facilities and the aquatic ecosystem into which they have been incorporated. The method of quantification involves a probabilistic systems approach which includes a due regard for the vagaries of nature. Essentially calculated is the change in desirability to man of the ecosystem as influenced by the losses of organisms, such losses being computed from the probabilistic curves of affected populations convolved with the probability of impact curves. Predictive techniques are developed for the avoidance of mortalities due to thermotoxic synergisms. A discussion of an atmospheric model counterpart is presented to demonstrate the existence of compatible and consistent atmospheric quantification procedures. This project is primarily intended as a state-of-the-art survey of the research areas contributing to this area with particular attention paid to the precise input modeling techniques available. However, a new method is presented for combining these inputs in a thorough and consistent manner to obtain a meaningful environmental impact measure.