Published May 20, 2024 | Version v1
Dataset Open

Daily and hourly noise pollution metrics measured at 146 locations in Accra, Ghana for 2019 – 2020 (Clark et al Scientific Reports 2021)

  • 1. ROR icon St George's, University of London
  • 1. ROR icon Imperial College London
  • 2. ROR icon University of Massachusetts Amherst
  • 3. ROR icon University of Ghana
  • 4. ROR icon University of British Columbia
  • 5. ROR icon McGill University
  • 6. SLR Consulting

Description

Daily and hourly noise pollution metrics measured at 146 locations in Accra, Ghana for 2019 – 2020 (Clark et al Scientific Reports 2021)

Citation: Clark, S.N., Alli, A.S., Nathvani, R., Hughes, A., Ezzati, M., Brauer, M., Toledano, M.B., Baumgartner, J., Bennett, J.E., Nimo, J. and Bedford Moses, J., 2021. Space-time characterization of community noise and sound sources in Accra, Ghana. Scientific reports11(1), p.11113

Link to publication: https://www.nature.com/articles/s41598-021-90454-6

Datasets include sound level measurements collected at 146 sites across the Greater Accra Metropolitan area (GAMA, based on 2010 census boundaries) in 2019/2020 by the Pathways to Equitable Healthy Cities research team (https://equitablehealthycities.org/ ). Continuous measurements were collected at 10 sites for 1 year (long-term), or at 136 sites for weeklong periods (short-term). Sound levels are A-weighted. Lday was calculated with respect to day-time hours between 6:00–21:59 and Lnight between 22:00–5:59. Lden was calculated with respect to day-time hours between 6:00–18:59, evening between 19:00–21:59, and night-time between 22:00–5:59.

 

See the attached publication for further information on this data.

 

What is included in this data upload. 

Two datasets of daily summarised sound level metrics:   

Day.long.csv:  daily sound metrics calculated on long-term measurement sites (n = 10) 

Day.short.csv: daily sound metrics calculated on short-term (weekly) measurement sites (n = 136)

Variables 

  • ·       date: date data was collected
  • ·       ID: unique site identifier
  • ·       LAeq24hr: 24-h equivalent continuous sound level (dBA)
  • ·       LDay: Day-time equivalent continuous sound level (dBA)
  • ·       LNight: Night-time equivalent continuous sound level (dBA)
  • ·       LDEN: day-evening-night sound level (dBA)
  • ·       IR.night: Intermittency ratio (%) during the night-time hours  
  • ·       IR.day: Intermittency ratio (%) during the day-time hours  

 

Two datasets of hourly summarised sound level metrics:  

Hr.long.csv: hourly noise metrics calculated on long-term measurement sites (n = 10) 

Hr.short.csv: hourly scale noise metrics calculated on short-term (weekly) measurement sites (n = 136) 

Variables

  • ·       date_hour: date and hour that data was collected
  • ·       ID: unique site identifier
  • ·       LAeqhr: 1-hr equivalent continuous sound level (dBA) 

Two datasets include contextual information for each measurement site and measurement period:  

site_info_long.csv: Contextual information on the measurements at long-term sites and latitude and longitude coordinates. Can be linked to sound level csv’s (above) via site ID

site_info_short.csv: Contextual information on the measurements at short-term sites and latitude and longitude coordinates. Can be linked to sound level csv’s (above) via site ID

Variables

  • ·       ID: unique site identifier
  • ·       Lat: Latitude in decimal degrees
  • ·       Lon: Longitude in decimal degrees
  • ·       Start_date: start date of measurements
  • ·       Start_time: start time of measurements
  • ·       End_date: End date of measurements
  • ·       End_time: End time of measurements
  • ·       Site_type:

o   Low-dens: Low or medium density residential

o   Commercial: Commercial, traffic, or industrial

o   High-dens: High-density residential

o   Other: Rural site

  • ·       Height: Height of monitors placed off the ground in meters
  • ·       Monitor placement: location monitor was placed
  • ·       Nearest_facade: nearest façade

Files

Day.long.csv

Files (3.5 MB)

Name Size Download all
md5:cf464b25b70093d044e2d3c82f82939b
287.3 kB Preview Download
md5:0bf7a662bb7977f2c0ed6e4d64a920f0
83.4 kB Preview Download
md5:3f515bde8f126e1b9809521483916c10
2.4 MB Preview Download
md5:5455b8951d09fca4d50e8ca2c6e54895
735.1 kB Preview Download
md5:12990295e738f528ce151696acefe0b6
18.4 kB Download
md5:e01a402fe14f6589de97b7d6207e7a7e
578 Bytes Preview Download
md5:a1bb3c2709e85a89384728654fedc051
11.8 kB Preview Download

Additional details

Related works

Is continued by
Publication: 10.1016/j.envres.2022.113932 (DOI)

Dates

Available
2021-05-27