A Pareto approach to Environmentally-Conscious Design and Manufacturing (ECDM) was developed and implemented for design of first-stage chloroorganics formation and lignin removal processes in Cl2/ClO2 softwood kraft pulp bleaching. A new model, the "(C+D) Model", was developed to quantitatively simulate first-stage chemical reactions leading to chloroorganics formation and lignin removal. This model was parameterized against published chemical speciation data from Cl2/ClO2 pulp bleaching experiments and commonly-observed qualitative delignification trends. The parameterized model predicted experimental measurements used in parameterization with accuracy similar or superior to other published bleaching models and realistically depicted global bleaching trends. A (C+D)EDED bleach plant simulation was developed using the (C+D) Model to predict first-stage processes and literature models to simulate latter stages. This plant simulation predicted design criteria of first-stage chloroorganics formation, chemical cost, brightness, and production rate arising from first-stage design specifications and production and brightness targets. Pareto design investigations identified design configurations yielding concurrent improvements in design criteria. Improved Pareto sets of design alternatives were generated using a Pareto Genetic Algorithm. Pareto sets how design of first-stage processes dictated tradeoffs between criteria. Final selection of preferred design alternatives within Pareto sets requires relative valuation of objectives to be specified. Valuation is uncertain when comparing incommensurate objectives, such as in environmental valuation. Tradeoff analysis was developed to assist explicit valuation of bleaching design criteria by identifying ranges of objective valuations for which each alternative in a Pareto set was preferred. Potentially-preferred alternatives could then be identified based on robustness against valuation uncertainty. This research realized a specific application of a general Pareto-based vision of ECDM. This general vision targets three common issues in ECDM: (i) directly addressing all processes influencing criteria during design, (ii) searching for design alternatives that are concurrently-improved in all criteria, and (iii) decoupling search and valuation to facilitate sensitivity analysis of alternative preference against valuation uncertainty. Future applications in other specific design cases may ultimately show the value of this vision in explicitly addressing these three ECDM issues.