physics.comp-phOct 10, 2026

FDTD Model of Noise Pollution from an AI Data Center

Authors: Gavin Buxton

Organizations: Science Department, Robert Morris University, Moon Township, PA 15108, US.

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Abstract

The sudden growth in AI data centers is raising numerous environmental concerns. Low-frequency noise pollution is a concern for local residents, that may not just be an annoyance but also carry significant health impacts. An FDTD model of sound propagation over the topography near an AI data center is presented. The topography plays a large role in the level of noise pollution, with areas of sudden elevation on either side of the river near the AI data center more susceptible to high noise levels, while areas further afield largely protected from noise pollution by the topography. Understanding the role that topography plays in noise pollution, and capturing the noise pollution in specific topographies, can help identify areas where noise mitigation strategies might be best employed.

Figures & tables

Figure 1: a) The elevation in a 5\text{\,}\mathrm{km}$\times$5\text{\,}\mathrm{km} region surrounding the AI data center and a visual representation of the angles of one-dimensional profiles used in the two-dimensional FDTD model. b) The predicted sound level and elevation as a function of distance from the AI data center. The sound is assumed to be 100 dB100\text{\,}\mathrm{d}\mathrm{B} a distance of 10 m10\text{\,}\mathrm{m} from the center of the site, and the effects of vegetation and temperature gradients are not included. The elevation data (and coloring) correspond with the above contour plot at an angle of 140 \SIUnitSymbolDegree140\text{\,}\mathrm{\SIUnitSymbolDegree} (extending through the center such that negative distances are towards 320 \SIUnitSymbolDegree320\text{\,}\mathrm{\SIUnitSymbolDegree} ).
Figure 2: The predicted sound level as a function of distance from the AI data center. The two-dimensional contour is interpolated from 180 FDTD simulations; a 2D simulation at every angle from the center of the site. The sound is assumed to be 100 dB100\text{\,}\mathrm{d}\mathrm{B} a distance of 10 m10\text{\,}\mathrm{m} from the center of the site, and the effects of vegetation and temperature gradients are not included. Red is 80 dB80\text{\,}\mathrm{d}\mathrm{B} , green is 53.3 dB53.3\text{\,}\mathrm{d}\mathrm{B} and blue is 26.6 dB26.6\text{\,}\mathrm{d}\mathrm{B} .
Figure 3: The effects of vegetation on sound levels. a) The porosity and modified density as a function of height that is assumed in areas where trees are present. b) The effects of flow resistivity, which varies linearly from these values at the floor to zero at 15 m15\text{\,}\mathrm{m} , on the sound level as a function of distance from the site.
Figure 4: The effects of temperature gradient in the air. a) The sound level as a function of distance from the site as a function of temperature gradients from −12 \SIUnitSymbolCelsius/km-12\text{\,}\mathrm{\SIUnitSymbolCelsius}\text{/}\mathrm{km} to 12 \SIUnitSymbolCelsius/km12\text{\,}\mathrm{\SIUnitSymbolCelsius}\text{/}\mathrm{km} . b) The sound level as a function of distance from the site showing the small changes in dB predicted as a function of temperature gradients at a location across the river from the AI data center.

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