Numerous relationships between noise exposure and transportation noise-induced annoyance have been inferred by curve-fitting methods. The present paper develops a different approach. It derives a systematic relationship by applying an a priori, first-principles model to the findings of forty three studies of the annoyance of aviation noise. The rate of change of annoyance with day-night average sound level (DNL) due to aircraft noise exposure was found to closely resemble the rate of change of loudness with sound level. The agreement of model predictions with the findings of recent curve-fitting exercises (cf. Miedma and Vos, 1998) is noteworthy, considering that other analyses have relied on different analytic methods and disparate data sets. Even though annoyance prevalence rates within individual communities consistently grow in proportion to duration-adjusted loudness, variability in annoyance prevalence rates across communities remains great. The present analyses demonstrate that 1) community-specific differences in annoyance prevalence rates can be plausibly attributed to the joint effect of acoustic and non-DNL related factors and (2) a simple model can account for the aggregate influences of non-DNL related factors on annoyance prevalence rates in different communities in terms of a single parameter expressed in DNL units-a "community tolerance level."

Fidell et al. [(2011), J. Acoust. Soc. Am. 130(2), 791-806] have shown (1) that the rate of growth of annoyance with noise exposure reported in attitudinal surveys of the annoyance of aircraft noise closely resembles the exponential rate of change of loudness with sound level, and (2) that the proportion of a community highly annoyed and the variability in annoyance prevalence rates in communities are well accounted for by a simple model with a single free parameter: a community tolerance level (abbreviated CTL, and represented symbolically in mathematical expressions as L(ct)), expressed in units of DNL. The current study applies the same modeling approach to predicting the prevalence of annoyance of road traffic and rail noise. The prevalence of noise-induced annoyance of all forms of transportation noise is well accounted for by a simple, loudness-like exponential function with community-specific offsets. The model fits all of the road traffic findings well, but the prevalence of annoyance due to rail noise is more accurately predicted separately for interviewing sites with and without high levels of vibration and/or rattle.

In 1981, Working Group 84 of the National Research Council, Committee on Hearing, Bioacoustics and Biomechanics, recommended C-weighted sound exposure and day-night average C-weighted sound level for assessment of high-energy impulsive sounds such as those generated by large military weapons, supersonic aircraft, and quarry or mining explosions. Studies conducted from about 1960 to 1990 showed that a linear relationship, with a slope statistically different from 1, exists between the C-weighted sound exposure level "CSEL… of a high-energy impulsive sound and the A-weighted sound exposure level "ASEL… of a non-impulsive control sound of equivalent annoyance. The slope was of the order of 0.5; i.e., a 1-dB change in the CSEL of high-energy impulsive sound corresponds to about a 2-dB change in the ASEL for a control sound of equivalent annoyance. Because of the non-unity slope, it is recommended that high-energy impulsive sounds be assessed by the level of an ''annoyance unit.'' Annoyance units double when the number of acoustical events double, but annoyance units quadruple when the C-weighted sound exposure doubles. © 1994 Institute of Noise Control Engineering.

Noise complaints received Army-wide for a one-year period were analyzed (a) to determine the relationship between the nature of the complaint and the type of noise and (b) to determine the relationship between complaints and the day–night level (DNL). For blast noise, 77% of complaints mentioned vibration or physical damage or both, thus confirming the validity of the C-weighted DNL as a better measure of blast noise than the A-weighted DNL. The relationship between DNL and complaints, however, was a very weak one. Instead, the data confirmed an independent finding of a recent study of Air Force noise complaints—that complaints are generated by unusual rather than typical noise levels. Since a valid measure of community response to noise should be functionally relatable to the noise dose, complaints do not appear to be a good measure of the community response. To deal with the wide variability in the emotional tone of the complaints a psychological model was developed and tested. The implications of this model for how an airport or Army base should deal with complaints are discussed.

For at least four decades, there have been reports in scientific literature of people experiencing motion sickness-like symptoms attributed to low-frequency sound and infrasound. In the last several years, there have been an increasing number of such reports with respect to wind turbines; this corresponds to wind turbines becoming more prevalent. A study in Shirley, WI, has led to interesting findings that include: (1) To induce major effects, it appears that the source must be at a very low frequency, about 0.8 Hz and below with maximum effects at about 0.2 Hz; (2) the largest, newest wind turbines are moving down in frequency into this range; (3) the symptoms of motion sickness and wind turbine acoustic emissions "sickness" are very similar; (4) and it appears that the same organs in the inner ear, the otoliths may be central to both conditions. Given that the same organs may produce the same symptoms, one explanation is that the wind turbine acoustic emissions may, in fact, induce motion sickness in those prone to this affliction.

Day-night average sound level (DNL) and the relationship between DNL and community annoyance to noise are often presented to a community as part of a noise-assessment process, usually as established scientific fact. In reality, there is great scatter and variability in the attitudinal survey data that are the basis for the DNL-response relationship. As a result, there is significant uncertainty around the corresponding curves that are fitted to the data. This paper collects, tabulates, and compares recommended minimum DNL criterion levels for various types of communities and settings. The paper summarizes some of the recommended adjustments to DNL that are contained in ISO 1996-1:2003 and other factors that reduce the variations between predicted and reported community noise annoyance. The paper recommends that the appropriate DNL criterion level in residential areas should be between 50 dB and 55 dB. Differences between attitudinal survey data on community annoyance and predicted community responses can be minimized by use of adjustments, most of which are contained in ISO 1996-1:2003.

Assessment of the annoyance of combined noise environments has been the subject of much research and debate. Currently, most countries use some form of the A-weighted equivalent level (ALEQ) to assess the annoyance of most noises. It provides a constant filter that is independent of sound level. Schomer [Acust. Acta Acust. 86(1), 49-61 (2000)] suggested the use of the equal loudness-level contours (ISO 226, 1987) as a dynamic filter that changes with both sound level and frequency. He showed that loudness-level-weighted sound-exposure level (LLSEL) and loudness-level-weighted equivalent level (LL-LEQ) can be used to assess the annoyance of environmental noise. Compared with A-weighting, loudness-level weighting better orders and assesses transportation noise sources, sounds with strong low-frequency content and, with the addition of a 12-dB adjustment, it better orders and assesses highly impulsive sounds vis-a-vis transportation sounds. This paper compares the LLSEL method with two methods based on loudness calculations using ISO 532b (1975). It shows that in terms of correlation with subjective judgments of annoyance-not loudness-the LLSEL formulation performs much better than do the loudness calculations. This result is true across a range of sources that includes aircraft, helicopters, motor vehicles, trains, and impulsive sources. It also is true within several of the sources separately.

This paper describes the measurement and analysis of over 11 000 blast recordings. These data are used to develop a statistical base for blast propagation and to establish one-third octave spectra for these blasts. These results can then be used to predict community blast noise levels. The blasts are divided into rather broad amplitude groupings and it is shown that received blast spectra are dependent only on grouping and not on absolute peak amplitude or distance (2–15 miles). One interesting result is that early in the morning and at far distances (normally over 5 miles) amplitudes are greatest upwind.