The HTML, interactive version of this document can be found here
I chose noise pollution around UM’s Coral Gables campus.
This area was selected because:
Noise pollution interferes with:
College students have to balance their time in necessarily quiet environments (studying, sleeping) and often louder environments (parties, dining halls, etc.). Understanding the nature of typical noise pollution on UM’s campus can provide a more in-depth picture of the settings in which students spend the majority of their time.
The data was collected from a purposive sample. This selection method makes sense for the intent to get a picture of noise pollution at places frequented by UM students, which is more meaningful for the purpose of this monitoring effort. Unfortunately, this sampling method does not allow for data to be generalized to the greater 33146 ZIP code and is less robust than random sampling methods.
Nine sites were intentionally chosen: 4 residential centers on/off-campus and 5 class/study areas.
Interactive map can be found here
The sources of noise pollution can be found by clicking through the mapped points, but are also listed below:
| Name | Noise | Sources |
|---|---|---|
| Red Road | 64.5 | Traffic (rush hour), many cars driving around |
| University Village | 73.6 | Traffic (Campus shuttle, beeping traffic), Many people, Other (AC units) |
| Richter | 67.3 | Other (birds chirping) |
| Campo Sano Construction Site | 76.3 | Other (air conditioning units) |
| Schwartz Center | 67 | Other (air conditioning units) |
| IT Building | 59.7 | Other (birds chirping, AC Units) |
| MP Dining Hall | 66.8 | Traffic, Many people |
| Stanford Circle | 67 | Traffic (Campus shuttle) |
| LSV/Metro | 63 | Traffic (Ponce & US-1), Other (Metro) |
Sampling was limited by (1) areas accessible by car (2) locations that were frequented among students on campus. It was also limited by the time of day, rush-hour. While this time of day is optimal for trying to collect traffic-related noise pollution, it doesn’t capture any indoor noise pollution, most construction work, or landscaping work. Using an app to record the extent of noise pollution gave the data a more objective measure than simple human observation, but the app was free in the AppStore and may not be the most accurate tool for measuring sound.