How much louder are big cities?

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

Let’s have a look at the quietest and loudest cities in the U.S. To give you a broader perspective, only the top values are listed for each Census division. In order to compare the listed numbers, please keep in mind that a 10dBA difference is perceived as doubling the loudness. So the average background noise level of 50dBA (typical for big cities like Las Vegas or Los Angeles) can be described as four times the loudness of a quiet town (30dBA).

One thing is apparent from the map: All of the noisiest cities in the U.S. are also among the cities with the highest population densities. To further illustrate this, we can draw a scatterplot. It shows us that on average, a tenfold increase in the population density leads to a 6.6dBA increase in the background noise level (perceived as approximately 60 percent louder).


The R-squared statistic (the percentage of variation in noise levels explained by population density changes) here is very high: a tad above 50 percent.

So perhaps we should really be interested in the residual values. In other words, how much noisier (or quieter) are certain American cities than one would expect judging only by their population densities?

Here's the map showing the aforementioned residual values county-by-county (you can zoom in on any state).

Las Vegas, New Orleans and Oklahoma host the most populated cities that are unexpectedly loud (the extra noise level is around 5dBA on average).

Unfortunately, there are no large cities on the other end of the spectrum. Here we see cities like Napa, CA and Santa Fe, NM, which can be 6-7dBA quieter than predicted by our model. The only relatively large metropolitan area where the noise level is lower than predicted is Honolulu, where the noise level averages below 45dBA despite a relatively high population density.


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About Andrey Kamenov

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

Andrey Kamenov is a data scientist working for Advameg Inc. His background includes teaching statistics, stochastic processes and financial mathematics in Moscow State University and working for a hedge fund. His academic interests range from statistical data analysis to optimal stopping theory. Andrey also enjoys his hobbies of photography, reading and powerlifting.

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