Calibration of low-cost sensor data for ambient PM_2.5 monitoring across urban and rural settings in South Central Uganda.

ABSTRACT: Air pollution is a leading risk factor for the global burden of disease. There are limited data from Sub-Saharan Africa (SSA). This study addresses significant data gaps in air quality monitoring in South-Central Uganda. Using a near-reference grade monitor and a network of 27 low-cost air quality monitors in the rural Rakai region and urban cities of Masaka and Kampala, we developed a locally tailored calibration model for ambient PM_2.5 concentrations. Using calibrated data across all low-cost monitors, we then examined spatiotemporal trends in ambient PM_2.5 concentrations. The calibration model, which adjusts for relative humidity, demonstrated robust performance with an R² of 0.92, a root mean squared error (RMSE) of 3.83 µg/m³ and bias of -0.

SUBMITTER: Le S 

PROVIDER: S-EPMC12671985 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature