Spatiotemporal Variation of PM_2.5 Concentration and Health Impacts in Addis Ababa, Ethiopia: Trends and Patterns

This study investigated the spatiotemporal variability of fine particulate matter (PM_2.5) in Addis Ababa, Ethiopia and assessed its associated health risks and economic burden using data from January 2022 to December 2023. Hourly PM_2.5 concentrations were collected through a hybrid monitoring network comprising seven low-cost sensors and two Beta Attenuation Monitors (BAM). Spatiotemporal analysis was performed using Python, and health risks were assessed by estimating the Hazard Quotient (HQ) and Excess Lifetime Cancer Risk (ELCR). The economic burden attributable to PM_2.5 exposure was assessed by monetizing disease-specific Disability-Adjusted Life Years (DALYs) using a locally adapted Value of Statistical Life (VSL) approach. Over the two-year periods, mean PM_2.5 concentrations ranged from 15 to 33 μg/m³ across monitoring sites, with an overall a citywide average of 27 μg/m³, exceeding the World Health Organization (WHO) Air Quality Guideline (AQG) of 5 μg/m³ by more than fivefold. Seasonal analysis revealed elevated PM_2.5 concentrations during the wet season (Kiremt), while diurnal patterns showed peaks of 38 µg/m³ at 7:00 AM. The HQ values for all age groups exceeded the acceptable threshold of 1, indicating non-carcinogenic health risks. ELCR estimates calculated using a slope factor of 0.008 exceeded the risk threshold (1 ×10^-4), whereas estimates based on the slope factor of 0.0012 remained within the acceptable limits, highlighting the sensitivity of cancer risk estimates to the toxicity parameter applied. The economic burden attributable to PM_2.5 exposure was estimated at USD 652.95 million over the two-year study period, contributing an external cost share to national GDP of 0.25% in 2022 and 0.25% in 2023. Cardiovascular diseases, particularly ischemic heart disease (IHD), accounted for the largest share of economic losses, significantly exceeding acute respiratory infections and PM_2.5 related cancers. These findings provide evidence to support targeted policies aimed at reducing PM_2.5 related cancers combined.