## Wednesday, September 22, 2010

### Measuring and Mapping Noise

After a few foggy days looking at visibility I dragged the blog into the noisy world of horns and train whistles. Today i've chosen the topic of measuring noise.

(This is turning out to be a very tricky thing, highly demanding of concentration and math skills. It's more troublesome than measuring the heat of chili peppers!)

Noise is sound waves (fluctuating air pressure) bouncing down the tiny channels in our ears and striking our ear drums. It's a very complicated thing to measure. One well-known unit of noise measurement is the decibel (one-tenth of a bel). Noise measurement units - indeed the whole process - are specially-adapted to measure only what people hear. That's not quite the same as measuring ALL the actual air pressure changes around us (noise).  Many sounds that might be heard by a dog, or bat, or microphone are not audible to us, so we intentionally filter them out during our measuring process.

We measure instantaneous noise, but average sound pressure is also important. It's a "weighted average" of the instantaneous measurements over time. This cumulative noise is what wears out our eardrums, causing us eventually to suffer hearing loss.

Sheesh. Even as I write this I realize what a complex subject this is. Probably too much for elementary mathematics, but ... if you want a nice overview of the decibel, you can read about it on Wikipedia.  Here's a preliminary definition:

decibel (dB) is a logarithmic unit that indicates the ratio of a physical quantity (power or intensity) relative to a specified reference level. A ratio in decibels is ten times the logarithm to base 10 of the ratio of two power quantities. Because this is a ratio of two measurements of a physical quantity, it is a dimensionless unit

Well, of course it is. Hmmm (I hummed quietly).

Okay, let's assume we did measure some noise - how could we best display our findings?

1. Measure noise in lots of places, over a long period of time, calculate the average noise levels and spread your findings on a map - you would have this plot of the noise around San Diego airport.

The airport is the yellow area in the center. Other colors around the map reflect industrial buildings, parkland, homes, etc. If you live outside these areas then airport noise is an insignificant part of your average daily noise intake (are there minimum daily requirements?).

2. Use special software to take those same measurements and you might get a three-dimensional, computer-generated noise map. This one came from the China Daily newspaper. It shows a neighborhood in Shenzhen China.

3. Here's an interesting way to show an aircraft's acoustical footprint. The odd shapes visually portray the noise of planes landing and taking off.

Patterns in orange represent noisy aircraft - they are no longer aloud (sorry, couldn't resist) in the US. Blue patterns are quiet planes. Numbers above each graphic are square miles of noise impact, and percentage of the aircraft landing at Chicago O'Hare; numbers below are plane model and passenger seating capacity. This presentation shows you to identify planes making the most noise per passenger. Of course you have to do this for each and every variant of aircraft. Not all are shown here.

4. Here's an FAA chart with two different plots. The rear (reddish) shows the number of people flying [passenger emplanements?!]. The front (greyish) shows the number of people affected by excessive airport noise. All the numbers are in millions.

Over 30 years, the number of people exposed to aircraft noise diminished rapidly as passenger numbers have increased gradually.

5. No more. Going any deeper into this noise business will take more mathematics than we can teach in Excel Math...