Expression Of Annoyance Three Letters

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Expression Of Annoyance Three Letters

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Received: 29 January 2020 / Revised: 14 February 2020 / Accepted: 15 February 2020 / Published: 20 February 2020

Sixty-one social studies on road traffic noise annoyance conducted worldwide over a forty-five-year period were reanalyzed by various means for possible temporal trends. Eighteen of these surveys were conducted after 2000. It appears that people’s reactions to road traffic noise were stable throughout the study period. No indications were found that would warrant a revision of the current EU reference curve for predicting road traffic noise annoyance.

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Some researchers claim that people today are more disturbed by road traffic noise than they were, say, 20-40 years ago [1, 2] among other things. Different subsets of recent and previous annoyance surveys and different data analysis techniques have been used to justify such a claim.

Disturbance caused by traffic noise is generally considered to be proportional to its long-term, cumulative noise level, but the prevalence of a subsequent degree of disturbance caused by traffic noise varies considerably from one study site to another.

Annoyance is expressed either on a linear scale ranging from no annoyance to the most extreme annoyance, or, as is common practice for regulatory purposes, on a scale indicating the proportion of the exposed population who consider themselves “very annoyed”, HA. . Highly annoyed refers to the top 28% of the annoyance scale. The results of the noise disturbance survey are presented as the percentage of very disturbed people at a given level of noise exposure. This treatment of noise exposure and annoyance values ​​can be traced back to Schultz [3] and FICON-US Federal Interagency Committee on Noise [4] who stated that “Annoyance is the preferred sum measure of people’s general negative reaction to noise , and that the proportion of the area’s population characterized as ‘very disturbed’ by long-term noise exposure is his preferred measure of disturbance’.

= 60 dB, the prevalence of highly disturbed residents can vary from 0% to 60% or more. In contrast, a prevalence rate of 10% very disturbed has been associated in various studies with noise levels ranging from about L

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= 75 dB. Therefore, the analysis of temporal trends in the annoyance response is highly dependent on the subset of survey data analyzed.

This paper analyzes a large set of reported research on road traffic noise annoyance and compares the results of different analysis techniques reported in the scientific literature.

A database was compiled from surveys conducted in the period 1969-2014. References to older research were mainly found in [5]. Information on more recent research (after 2008) was collected through direct searches of journal articles and conference proceedings. Only survey reports providing information on noise exposure levels and the corresponding prevalence of highly disturbed residents were considered.

No distinction was made between the two common metrics of cumulative transport noise exposure, DNL and DENL, as Brink et al. [9] found that the difference between them was less than 0.5 dB for road traffic noise.

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Table 1 shows the 61 studies that were included in the current analysis, 18 of which were conducted in the last two decades.

The table lists the different studies by year of implementation. The “code” column refers to the survey codes in [5]. This catalog assigns a unique identifier to most noise surveys conducted before 2008 for easy identification. The “EU” column indicates which studies were included in the Miedema and Vos [52] analysis of the exposure-response curve currently used in the EU. In addition to the total number of respondents, the table also lists the calculated community tolerance level – CTL value and r

The total data set comprises about 600 paired observations of noise exposure and the prevalence of high anxiety, based on the opinions of about 95,000 respondents in a social survey. More detailed information on the individual surveys can be found in the references provided (see separate list at the end).

The results of research on noise disturbance are usually presented as exposure-response relationships, also commonly called dose-response or dose-response functions. The results are plotted with the independent variable, noise exposure, measured as DNL, ​​DENL or a similar quantity, on the horizontal axis and the prevalence of annoyance on the vertical axis.

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Researchers who rely solely on regression analysis to support their conclusions usually enter all data from field observations into standard statistical analysis software (eg, SPSS-Statistical Package for the Social Sciences) and accept the result as definitive. -answer without trying to provide a logical explanation of the results and regardless of the implications of their analyses.

The results of the analysis of individual noise nuisance surveys can be presented in different ways. This is especially true with respect to exposure information. Responses may be grouped into noise exposure bins, typically 5 dB wide, or a group of respondents may be characterized by the noise level at a centrally located observation point. Therefore, the number of paired data points can vary significantly from one study to another.

Some researchers prefer to analyze each survey individually. A regression function is fitted to the survey data and this function is used to calculate the response to specific exposure levels. A second-order polynomial regression function is then calculated to approximate the combined results from different surveys.

A second-order polynomial function usually has a minimum (or maximum) value in the appropriate exposure range. This contradicts the assumption that the startle response increases monotonically with increasing levels of noise exposure. Some researchers prefer other functions, (typically exponential or logistic) or adjust the low end of the calculated exposure-response curve to support a logical explanation of the results. In developing the reference curve used by the EU, for example, Miedema and Vos [52] forced the regression curve through zero at exposure level L

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= 42 dB, consistent with their observations. The logistic function assumes that the annoyance response asymptotically approaches the endpoints 0% and 100% very annoyed.

This method of analysis was introduced by Fidel et al. [53] and Schommer et al. [54] and is described in the international standard ISO 1996-1 [55]. The shape of the exposure-response function is fixed in the CTL analysis, rather than being derived from a curve fitting analysis. Its form is based on the observation that the rate of change of annoyance with DNL closely resembles the rate of change of loudness with sound level. The CTL approach accounted for half as much variance in the relationship between noise exposure and nuisance prevalence rates in communities as conventional analyzes [53].

, for a survey is the predicted value of the noise level, DNL or DENL, at which half of the survey respondents report high distress from noise exposure. Large CTL values ​​indicate a high tolerance for noise exposure in the community, while small CTL values ​​indicate a low tolerance for noise exposure. Differences between research findings can be characterized in units denominated in decibels through simple comparisons of CTL values ​​across communities. Therefore, the CTL method is well suited for time trend analyses. Changes in CTL value directly show how the prevalence of anxiety varies over time.

The CTL value is not a noise metric by itself; it is simply the DNL value at which (by convention) half the community is very disturbed by noise exposure (and the other half is not.)

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Some researchers question whether a common function of the type of CTL assay can be found at all [56]. “The goodness of fit,” that is. how well a function fits a set of data points is characterized by the coefficient of determination, r

Values ​​for the CTL function and second-order polynomial regression