Abstract:
Background: Bhubaneswar, a rapidly developing smart city in eastern India, faces persistent air quality challenges primarily due to vehicular emissions, construction, and industrial activities. Conventional monitoring in the city has been limited to a few fixed stations, providing insufficient spatial coverage to represent citywide pollution variability. Methodology: To address this gap, a dense low-cost sensor (LCS) network comprising 21 stations was deployed across Bhubaneswar's residential, traffic, and industrial zones. The network operated continuously for one year (2022-2023), and the LCS-based PM2.5 and PM10 data were validated against co-located gravimetric reference measurements and compared with MERRA-2 reanalysis datasets to assess performance and spatial representativeness. Major findings: The LCS-based PM2.5 measurements showed strong agreement with reference gravimetric data (r similar to 0.92), confirming the reliability of the network for long-term urban monitoring. The observed PM2.5/PM10 ratio (similar to 0.92) indicated a dominant contribution from fine anthropogenic particles. The network identified pollution hotspots near major highways and dense traffic corridors, where pollutant concentrations exceeded the National Ambient Air Quality Standards (NAAQS) for more than 50 % of the observation period. A notable positive weekend effect was observed across most stations, in contrast to trends reported for other Tier-II Indian cities. Conclusions: This study provides the first high-resolution, yearlong characterization of PM pollution in Bhubaneswar using a citywide LCS network. The results highlight the potential of low-cost sensing systems for cost-effective, scalable urban air-quality surveillance and support the formulation of targeted mitigation strategies for rapidly urbanizing regions in the Global South.
