Abstract: To minimize the environmental impact of electricity produced by clean coal combustion, several pollution control devices are proposed as Best Available Techniques (BATs). Reductions in particulate matter (PM), nitrogen oxides (NOx) and sulfur dioxide (SO2) emissions would reduce the global and local environmental impact but investment costs bottleneck their implementation. In this paper, a multi-objective optimization problem is formulated including economic, social and environmental metrics to support decision making in the selection of those pollution control technology devices that should be applied in practice. The design task is formulated as a bi-criteria mixed-integer nonlinear programming (MINLP) problem, the solution of which is defined by a set of Pareto points that represent the optimal trade-off between the two objective functions. Results show that investment strategies will differ when considering social or environmental objectives to be minimized.

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