Utility of low-cost sensor measurement for predicting ambient PM_2.5 concentrations: evidence from a monitoring network in Accra, Ghana.

ABSTRACT: Ambient air pollution has been linked to several health endpoints. The WHO attributes 7 million deaths annually to air pollution with particulate matter (PM2.5) being the pollutant of critical importance due to its devastating health effects. Air quality monitoring is very limited in sub-Saharan African (SSA) countries and although satellite remote sensing has helped to bridge the huge air quality data gaps, these measurements have not been validated against ground-level measurements in these countries. We therefore evaluated the efficiency of low-cost sensors in estimating PM2.5 concentrations in an African city through comparison of low-cost sensor data with satellite aerosol optical depth (AOD) data leveraging complex machine learning (ML) methods. Low-cost sensor data were collected fr

SUBMITTER: Attey-Yeboah P 

PROVIDER: S-EPMC12363562 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature