Temporal Sampling Requirements for Estimating the Mean Noise Level in the Vicinity of Military Installations
CONSTRUCTION ENGINEERING RESEARCH LAB (ARMY) CHAMPAIGN IL
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High sound exposure levels in the vicinity of military installations are an increasingly important acoustics problem, especially with the recent emphasis on the establishment of environmental standards. This research addresses the problem of using monitored data to establish estimates of long- term average noise levels which can be determined with prespecified levels of precision and statistical significance. Daily average noise-level data exhibit characteristics amenable to time series modeling. The Dynamic Data System DDS method is used to characterize noise data by autoregressive-moving average ARMA models for the purpose of determining the variance of the sample mean of such data so that sampling requirements can be derived. Daily average noise data from Los Angeles International, Boston Logan, Washington Dulles, and Washington National airports are analyzed to 1 ascertain the effects of operations, weather, and nonairport community noise on measured sound exposure levels and 2 derive associated sampling requirements for the estimation of the sample mean noise levels. General results indicate that 30 to 60 days of consecutive sampling are required to estimate the mean noise level with a precision of or - 50 percent of the sample mean at the 0.05 level of significance. To assess sampling requirements at Fort Bragg, a combined multiplicative operations and weather model is developed. Noise data based on artillery blast operations were predicated via a computer model for average weather conditions. A model which represents the day-to-day effects of weather or operations to develop the combined models.
- Statistics and Probability