Cost estimates in cost-effectiveness analysis of water quality monitoring systems

Abstract

Traditional cost-effectiveness analysis requires obtaining estimates of the cost and effectiveness of a monitoring program or design and weighing them against each other. With obvious technical soundness of the approach, its complete utilization, however, is still very limited. The limitations should be attributed firstly to the necessity to express both the cost of a monitoring program and its effectiveness in quantitative terms using at least the same measurement units, if the monetary estimates are not available. Although the cost estimation is considered as a simple technical exercise, it is worth noting that comprehensive and systematic guidelines for developing cost estimates of an environmental monitoring program are not available. In most of the cases, when evaluating the cost of a monitoring program, the authors take into account only some of the components and even for those components estimates are very approximate or are not available at all. When monetary estimates of the effectiveness and the cost of a monitoring program are unknown, the direct cost-effectiveness analysis can be replaced by an operation research model, solutions to which generate efficient monitoring designs. One of the two possible articulations of the optimization problem is to minimize the cost of a program or design, so that the effectiveness of the program meets established requirements. In this case, mathematical articulation of the cost serves as the goal function. The effect of a particular expression for this function on the designs developed as solutions of the constraint optimization problem is investigated in the study. The analysis of the scientific and technical literature on cost-effectiveness analysis of environmental and ecological monitoring programs revealed different approaches to cost estimates with the emphasis on the necessity to distinguish between budgetary costs, showing how the allocated money is spent and economic costs which broaden the consideration and add the opportunity cost, i.e. the missing benefits of other activities due to allocating the money to monitoring an environmental resource. The comprehensive cost assessment should include both components, however, the approaches to complete cost estimates are yet to be developed. Since the cost function is intended for application in the operation research model for developing efficient temporal monitoring designs, only budgetary cost is considered under an assumption that variable cost is associated solely with water sample collection and processing. The rest of the cost components are independent of the number of taken samples and constitute the fixed cost. In all suggested approaches, the cost of a program is defined as a non-negative, non-decreasing function of the number of samples collected or observations made. Seven mathematical expressions were developed with the same properties and their parameters were identified based on rough estimates of the costs of operations of a water quality monitoring system. The effect of the cost articulation on the developed designs was investigated through a series of computational experiments, where the designs were developed as solutions of the optimization problem with different mathematical expressions for the goal function. The results of computations showed that the solutions of the optimization problem are invariant of the expressions used for the cost function. The designs for monitoring water constituents remained unchanged when the developed expressions with different mathematical functions were substituted into the cost function. The study showed that, the optimal number of observations is independent of the cost of a monitoring design. It is determined by the level of effectiveness which must be attained by the design. The results validate the replacement of the cost-effectiveness analysis in its classical form by an operation research model which minimizes the total number of observations with the limit set for required effectiveness. Solutions of this model will generate designs with minimal cost.