USING CUMULATIVE NOISE EXPOSURE (CNE) MODELS TO COMPARE MANAGEMENT SCENARIOS IN NATIONAL PARK UNITS

Since its inception in 2000, the National Park Service (NPS) Natural Sounds Program (NSP) has worked with parks nation-wide to address management issues concerning the acoustical environment. The NSP is a resource for parks that do not have staff with acoustical expertise. The NSP receives requests to assist with monitoring efforts, data analysis, and data synthesis. Typically, monitoring data have been distilled into a suite of metrics that describe various aspects of the current acoustical environment. As concerns about noise management have diversified, many parks have become interested in exploring future scenarios and potential effects of management options.

We will discuss the use of CNE modeling as a tool for resource managers. The NSP has been producing CNE models using two separate types of software. For road noise and point source models, the commercially available Computer Aided Noise Abatement (CadnaA) software can handle custom point and line source spectra, traffic count inputs, topography, and simple vegetation categories. The typical model output is a grid-based map of CNE. The output can be viewed as a 2D map, or as a 3D rendering of the same output (Figure 1). CadnaA has the ability to export results for post-processing using geographic information systems (GIS) software. Using GIS post-processing, quantitative comparison of current conditions against other scenarios is possible. Recently, CadnaA added a Traffic Noise Model (TNM) module, which may qualify it for use in Federal Highways Administration and other Department of Transportation noise modeling and mitigation projects.

For aircraft noise modeling and mitigation, Integrated Noise Model (INM) is the model required by the Federal Aviation Administration (FAA). Some complex scenarios can take several weeks to model in INM, a problematic delay which makes INM difficult to use for scenario development. The NSP has developed an Interactive Noise Forecast (INF) tool to augment the value of INM. INF ingests INM metrics from a suite of single aircraft scenarios (aircraft type and route), and enables rapid computations of aggregate noise exposure from arbitrary multiples and combinations of these input scenarios. INF produces noise impact maps displaying multiple metrics for each point (Figure 2). With a runtime on the order of minutes, INF is an excellent tool for exploring possible alternatives. Planners and managers can use INF to consider how changes in traffic levels, or the proportions of different aircraft types composing the traffic, could affect CNE. INF is implemented in R, an open source data analysis program.

Management of the acoustical environment is a burgeoning topic within the National Park Service. Models such as CadnaA, TNM and INM offer sophisticated capabilities for realistic, quantitative forecasts of noise exposure. The capacity to visualize noise exposure predictions provides a medium to express a surfeit of quantitative data in an intuitive and aesthetically appealing format. Evocative graphical renderings make noise models more approachable, and are an excellent way to convey complex information to resource managers and public audiences.

Figure 1. CadnaA 3D output from Glacier National Park

Figure 2. Example of INF output at Grand Canyon National Park