Noise Research

Useful metrics for analyzing aircraft noise

Other metrics are currently under investigation that might be useful for analyzing aircraft noise. However, they have been shown to be useful to demonstrate the effects of noise. These metrics include:

  • Respite
  • Effects Mapping


What is respite? Does it mean:

  • Total relief from any aircraft event for an hour, a morning, or an early evening?
  • Relief from aircraft events that would otherwise interfere with outdoor activities?

Obviously, respite can be locally defined to fit the needs of any community or study area. It depends on the nature and frequency of the aircraft operations.

To provide a measure of respite, histograms or tables may be used to highlight sound level variations or the number of events over time. This type of analysis could include:

  • A "Number-of-events Above a Specified Sound Level" (NA) analysis for a low-level threshold (perhaps 60 dB Lmax)
  • A "Time Above a Specified Sound Level" (TA) analysis for a low-exposure threshold
  • Equivalent Sound Level (Leq) and Maximum A-weighted Sound Levels (Lmax) calculations on hourly intervals during an average day (or, perhaps a busy/active day)

This analysis can be further refined to include only departures or arrivals for each runway. Note that this type of analysis requires hourly operations data for each runway.

How are Respite Metrics Used?

One way to measure "respite" from intrusive noise events is to use the metric "Median Quiet Interval (MQI)." It is the average time between aircraft events that exceed a selected threshold. To calculate MIQ for a selected threshold sound level, we:

  • Subtract the TA from the total time selected (for example, a 24-hour period)
  • Divide the remainder by the NA for that same threshold sound level (again, over the same 24-hour period).

For example, if an event is defined by:

  • TA65(30) (30 minutes or 0.5 hours per day above 65 dB), and
  • NA65(100) (100 events per day above an Lmax of 65 dB)

The MQI is 14.1 minutes. The calculation would be:

(24 hours total time - 0.5 hours above 65 dB) / (100 events above Lmax of 65 dB) = 0.235 hours or 14.1 minutes

In this example, there would be one event above 65 dB (with an average duration above that threshold of 18 seconds) occurring every 14.1 minutes. It is important to understand that this example assumes that 100 aircraft events (that exceed the 65 dB threshold for 30 minutes of a full 24-hour day) are equally spaced out in time over 24 hours.

In reality, aircraft events that rise above the 65 dB threshold are likely to occur more often during the day and less often during the night. In addition, the duration and level of each event (for example, TA) varies depending on:

  • aircraft type
  • make
  • model

Effects Mapping

When objective supplemental metrics such as Lmax or NAL(X) are used, there is an estimated dose-response relationship between:

  • the noise exposure expressed by the metric and
  • the resulting effect on people

For example, if you know the level of sound that begins to interfere with normal conversation, you can represent this as L(X). If you then attach NA to this representation, you get NAL(X). You can then interpret NAL(X) as the number of times aircraft sound will interfere with speech.

As with NAL(X), the average number of speech disruptions during an average day of operations also may be plotted as an Effect Map.

Effects mapping uses the average research data available, on annoyance, speech interference, and sleep disturbance. This averaged data is overlaid on a background map of a specific community or local airport maps. Those averages may overstate or understate the actual effects in a specific community. The method provides a visual approximation of effects in the vicinity of an airport. Figure 1 is an example of an Effect Map.

Map of Average Number os Speech Disruptions

Figure 1. Average Number of Speech and Communication Disruptions in a Typical Day Derived From Research Study Results

Similarly, you can use research study results to plot estimated contours or create metric tables to represent:

  • the number of people awakened
  • the percent or number of people annoyed
  • the number of schools where learning may be adversely affected

Strengths and Weaknesses of Effects Mapping

The strength of effects mapping is that it provides an alternative representation of how people may be affected by aircraft noise. You don't need to understand complex logarithmic metrics to understand an effects map. Effects maps can express complex relationships to physical metrics. For example, an effects map may express sleep disturbances during an entire night. This relates to:

  • the distribution of single noise events,
  • the time of night they occur, and
  • the different sensitivities of the population to awakening

The weakness of effects mapping is that it based on average reactions across large numbers of people, communities, and airports. Thus, the actual effects on any one person or community may differ considerably from these averages.

For additional information on effects mapping, click Here.

For information on sleep disturbance, click Here.

For related presentations see:

Technical Requirements

Most effects of interest may be estimated from the physical metrics available in the Noise Model INM: DNL, Leq, Lmax, and SEL.