Addressing Biases in Ambient PM<sub>2.5</sub> Exposure and Associated Health Burden Estimates by Filling Satellite AOD Retrieval Gaps over India
Varun Katoch, Alok Kumar, Fahad Imam, Debajit Sarkar, Luke D. Knibbs, Yang Liu, Dilip Ganguly, Sagnik Dey
Abstract
Ambient PM 2.5 exposure statistics in countries with limited ground monitors are derived from satellite aerosol optical depth (AOD) products that have spatial gaps. Here, we quantified the biases in PM 2.5 exposure and associated health burden in India due to the sampling gaps in AOD retrieved by a Moderate Resolution Imaging Spectroradiometer. We filled the sampling gaps and derived PM 2.5 in recent years (2017–2022) over India, which showed fivefold cross-validation R 2 of 0.92 and root mean square error (RMSE) of 11.8 μg m –3 on an annual scale against ground-based measurements. If the missing AOD values are not accounted for, the exposure would be overestimated by 19.1%, translating to an overestimation in the mortality burden by 93,986 (95% confidence interval: 78,638–110,597) during these years. With the gap-filled data, we found that the rising ambient PM 2.5 trend in India has started showing a sign of stabilization in recent years. However, a reduction in population-weighted exposure balanced out the effect of the increasing population and maintained the mortality burden attributable to ambient PM 2.5 for 2022 (991,058:798,220–1,183,896) comparable to the 2017 level (1,014,766:812,186–1,217,346). Therefore, a decline in exposure alone is not sufficient to significantly reduce the health burden attributable to ambient PM 2.5 in India.