The classic "A" weighted noise level measurement is often used worldwide as the sole criterion to specify and evaluate the environmental noise impact of proposed or existing sites.
This is the elephant in the global noise evaluation room. Noise ordinances and regulations too often simply set maximum daytime and nighttime dB(A) noise level requirements.
All too often, this results in a deluge of noise complaints from the local community, despite the regulatory noise levels being met.
The "A" weighting is a sound level meter frequency filter designed to evaluate how damaging a sound would be to your hearing. As your hearing is progressively less sensitive to lower frequencies, it progressively filters out low frequencies like a graphic equaliser used to turn down the bass.
Sound file: 100Hz, 300Hz and 1000Hz tones
Unfortunately, in the environmental wild, low frequencies travel the furthest, diffract round barriers, pass through windows with little attenuation and are a major cause of noise complaints. But the "dB(A)" criterion is largely deaf to these critical low frequencies, it doesn't measure them. This is the equivalent of looking at a rainbow through a filter that eliminates the colour red or designing a piano with the bottom 8 keys removed...
This plot shows how the filter works. The X axis is frequency or pitch, from low to high, the Y axis is amplitude (dB). The black (Z) line is unfiltered, the "A" filter (red line) progressively attenuates lower frequencies - down to 1/8000th of the level at 31.5Hz (-39dB), to 1/8th of the level at 250Hz (-9dB) whilst leaving 1000Hz unchanged. The typical "hum" frequency range is marked in orange (play the above sound file to hear examples).
dB(A) ignores the very hums that cause complaints
Data Center hum outdoors and indoors: 118Hz cooling fan tones
Listen to this recording that illustrates the impact of low frequency tonal noise from a Data Center in the community that meets the dB(A) requirements! Is that acceptable? Would you complain?
This plot shows the narrow band frequency analysis of the above recording. The large spike at 118Hz is the primary fan tone (plus lesser harmonics at x2 and x3). Passing this sound through windows progressively attenuates higher frequencies, making the hum even more dominant - and even more annoying as it's there 24/7 and you cannot escape by moving indoors. Imagine trying to sleep in that...
This narrow band frequency analysis plot shows the effect of a sound level meter "A" weighting on the Data Center noise signature. Comparing the weighted plot (red) with the "A" weighted blue trace shows how the filtering dramatically reduces the amplitude of the low frequency hum. In fact, in this case removing the hum tones only cuts the overall meter measured dB(A) by about 1dB, a negligible change that is within measurement error.
Without the hum, a certain dB(A) noise level and no complaints. With the hum, widespread complaints for a noise with exactly the same measured dB(A).
There are complex international standards covering this option, e.g. ISO BS4142 (Methods for rating and assessing industrial and commercial sound) + ISO / TS 20065 (Objective method for assessing the audibility of tones in noise – Engineering method).
Whilst they provide highly technical methods using sophisticated and expensive instrumentation, it's possible to get similar results very simply at zero cost and with little or no significant noise expertise.
In addition to complex narrow band analyses, BS4142 also suggests that tones can be evaluated by a) listening or b) using 1/3 octave analysis. Unfortunately, our experience is that people (even noise consultants) can be very bad at judging tones by ear and 1/3 octave analysis is ancient tech that is very unreliable as a tone detector.
The simple solution is to bypass both of these suggestions and use a free narrow band analysis app on a smartphone. This is not only simple, it is a reliable and accurate way to both detect and evaluate tones.
The basic principle is very simple. This plot shows a narrow band noise analysis (using professional analysis software) of a sound that includes a classic fan drone at 148Hz. To identify that there is a tone and to determine just how annoying it might be, the frequency resolution has been set to between c 2Hz and 3Hz for the analysis.
The sound sample is averaged over several seconds to give this result at the required location (e.g. at a site boundary or in the community). Eyeball the average broadband noise either side of the tone (the red line) and estimate the amplitude of the tone above this value as shown.
While these figures are approximate, they are infinitely better than using just dB(A), or listening, or using 1/3 octaves.
This simple analysis method can be used at no cost by anyone with a smartphone. This screenshot is of a similar analysis using a free Android FFT app and it gives the same result as the costly professional software shown above. There a fan tone at 148Hz that is around 10dB above the estimated broadband average (red line) so it is audible and complaints are possible.
We have tested numerous free Android apps and, whilst there are others, we have provided detailed guidance as to how to download and use our favoured spectrum frequency analysis app.
Regulators or local residents can use this approach very effectively to evaluate the character of environmental noise in addition to any formal dB(A) measurements. In addition to providing objective evidence of any tonal content in the sound, the results also provide invaluable diagnostic information to identify the precise causes of the tones. This makes it much easier to determine the options to mitigate the problem, which in turn, means that a rapid resolution is much more likely.
We use this approach to solve environmental noise problems across the planet quickly and without site visits.
We regularly run short webinars covering on the optimum approach to evaluate and solve noise complaints.
Accuracy
Noise instrumentation suppliers and many noise consultants do not like smartphone analysis apps. Whilst the reasons for the negativity of the former are fairly obvious, many of the latter do not use or understand FFT frequency analysis and are hung-up on calibration, frequency range linearity and other technicalities that are irrelevant for this application.
The proof lies in our success in using this approach for countless projects across the planet and in training many regulators who now use the techniques. You can view a detailed rebuttal of the arguments used by vested interests about the accuracy of smartphone frequency analysis apps.
Noise ordinances, specifications and regulations
This approach can be included very effectively in all of these applications to get results that are infinitely more reflective of the impact of environmental noise from any industrial or commercial site on communities compared with using just an all-to-prevalent simplistic dB(A) specification.