Assessment of PM2.5 deposition in the human respiratory tract from a hyperlocal dataset in Bhubaneshwar, India

Abstract

Air pollution is a leading environmental health risk in India, contributing to disease burden and mortality. Effective mitigation measures require high-resolution monitoring. This study leverages hyperlocal air quality data from 21 low-cost sensor (LCS) stations in Bhubaneswar (March 2023-February 2024) to assess spatiotemporal variations in PM2.5 . Additionally, the Multiple-Path Particle Dosimetry (MPPD) model was used to quantify wintertime PM2.5 deposition in the human respiratory tract across seven age groups. PM2.5 exhibited strong seasonal variation, peaking in winter and remaining elevated in post-monsoon. Persistent high-pollution regions, including Rasulgarh, Dumduma, Nandan Vihar, Patarapada experienced consistently high concentrations due to vehicular emissions, industrial activities, and biomass burning, emerging as persistent high-pollution regions necessitating year-round mitigation. Seasonal pollution hotspots - Kesora, Niladri Vihar, Sailashree Vihar experienced episodic PM2.5 spikes exceeding 20% of seasonal means, requiring targeted interventions. Dosimetry analysis revealed age-specific deposition patterns: infants and toddlers retained the highest PM2.5 in the head and tracheobronchial regions, increasing their risk of upper respiratory conditions, while children had the highest pulmonary deposition, posing long-term respiratory risks. Adults (> 49 years) exhibited lower pulmonary deposition but remained vulnerable to cumulative exposure effects. Lobar analysis showed predominant PM2.5 accumulation in the lower lung lobes across all age groups, with infants experiencing the highest deposition due to smaller airway diameters. These findings highlight the pressing need for targeted air pollution mitigation strategies in high-risk regions and among vulnerable populations to minimize long-term health impacts in the city.