While aircraft environmental performance has been important since the beginnings of commercial aviation, continuously increasing passenger traffic and a rise in public awareness have made aircraft noise and emissions two of the most pressing issues hampering commercial aviation growth today. This research explores the feasibility of integrating noise and emissions as optimization objectives at the aircraft conceptual design stage, thereby allowing a quantitative analysis of the trade-offs between environmental performance and operating cost. Beyond meeting regulations and establishing environmental performance trades, the design tool allows the generation of extremely low-noise and low-emissions designs that could, in the future, dramatically decrease the environmental impact of commercial aviation, albeit at the expense of increased operating cost. To these ends, a preliminary design tool was developed that uses a multiobjective genetic algorithm to determine optimal aircraft configurations and to estimate the sensitivities between the conflicting objectives of low noise, low emissions, and operating costs. The design tool incorporates ANOPP, a detailed noise prediction code developed at NASA Langley, and NASA Glenn's NEPP engine simulator, as well as aircraft design, analysis, and optimization modules developed at Stanford.