Predictions of noise disturbance near large airports

Abstract This report examines the relationship between public annoyance with aircraft noise, objective measures of the noise itself, and mediating social or psychological conditions which affect the noise-annoyance relationship. The noise readings and interviews were gathered in areas within 12 miles of the major airports serving Atlanta, Dallas, Denver and Los Angeles. A total of 4212 hour-long interviews were conducted in the survey period of May and June, 1967. Noise measurements were made shortly before and concurrent with interviewing in the sampled areas. The noise measures evaluated include the composite noise rating (CNR), and modified noise and number index (NNI), noise exposure forecast (NEF), and composite noise index (CNI). An additional measure of another type was also investigated: the cumulative time during the day in which the speech interference level (SIL) of aircraft noise exceeded certain values. From the analysis, it was apparent that CNR and NNI are essentially interchangeable, and are rather well correlated both with NEF and with the logarithms of the SIL duration measures. Seven major social-psychological predictors of annoyance are also identified. In order of importance (determined by their ability, in combination with the noise measures, to predict annoyance) the measures are: fear of aircraft crashing in the neighborhood; distance from the airport; susceptibility to noise; noise adaptability; city of residence; belief in misfeasance in the aircraft or airport industries; and the extent to which the airport is seen as important to the local economy. These variables, selected from 53 correlated predictors of annoyance, were found to be consistently the most powerful predictors of annoyance measure—annoyance, V—when used in conjunction with a noise predictor. Of the noise predictors studied, CNR proved to be the most stable in the presence of the social predictors. Based on this analysis, it is concluded that the generalized predictive equation for the revised measure of annoyance V will, within limitations imposed by the data and the assumptions from which it was derived, remove about 63% of the variance between predicted and observed mean values of V. In generalizing the annoyance model whose development is described here, it should be recognized that the data contributing to its derivation were obtained in large cities, in neighborhoods near major airport traffic patterns. Although the sampling design ensured sufficient stratification of economic, cultural, and ethnic groups, the extent to which the four airport situations studied are “typical” of the nation as a whole is not yet established.