The expected rise in aviation demand requires the reduction of the environmental impacts that impede this desired growth, such as fuel burn, emissions, and airport noise. A number of current technology programs attempt to identify, evaluate, and select the environmental technology solutions for the coming decades. Fleet-level evaluation will be essential to deciding between various technology options because it provides a system-level assessment that clarifies the effect of operational and policy variables. Fleet-level modeling in general, introduces various complexities, and detailed fleet-level models require significant time and computing resources to execute. With a large number of potential technology options available for assessment, a full detailed analysis of the technology space is infeasible. Therefore, a simplified fleet-level environmental evaluation methodology is required to select scenarios to carry forward for detailed modeling. Capabilities such as the Global and Regional Environmental Aviation Tradeoff (GREAT) tool, have achieved rapid simplified fleet-level analysis for fuel burn and emissions, but currently lack a satisfactory generic framework to evaluate fleet-level noise. The primary objective of this research is to formulate and implement a generic fleet-level noise methodology that allows decision makers to analyze the fleet-level impact of many technology scenarios on the quantity of noise, and also its distribution about certain airport types. This information can be leveraged to provide screening assessments of technology impacts earlier in the decision-making process, reserving more sophisticated modeling techniques for the most promising scenarios. The capability gaps identified are addressed by the development of a rapid generic fleet-level noise model that captures basic airport noise contour shape and contour area, a categorization of airports with respect to their operational and infrastructure characteristics, and the development of shape metrics that enable rapid classification and comparison of contour shapes. Once the capability gaps were addressed, the resultant System-Wide Assessment of Noise (SWAN) methodology was implemented via use cases to demonstrate the application of the methodology, examining the introduction of a set of possible near-term (N+1) future technologies into the forecast. While these examples are simplified and notional, they demonstrate the types of analyses and investigations that can be performed with the SWAN methodology, providing answers regarding the impact of technologies on contour shapes. The development, verification, validation, and demonstration of these capabilities complete a framework for evaluating fleet-level noise at the screening-level that retains the ability to capture and effectively discuss shape information beyond the capability of current screening-level noise evaluation techniques. By developing a rapid generic fleet-level noise model, a set of Generic Airports, and metrics that objectively quantify and describe shape, decision-makers can access greater levels of information, including the critical facet of contour shape in fleet-level airport noise.