Driving factors behind the continuous increase of long-term PM2.5-attributable health burden in India using the high-resolution global datasets from 2001 to 2020

Maji, Kamal Jyoti, Namdeo, Anil and Bramwell, Lindsay (2023) Driving factors behind the continuous increase of long-term PM2.5-attributable health burden in India using the high-resolution global datasets from 2001 to 2020. Science of the Total Environment, 866. p. 161435. ISSN 0048-9697

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Abstract

Air pollution is the fourth leading global risk factor, whereas in India air pollution is reported as the highest risk factor with millions of premature deaths every year. Despite implementation of several air pollution control plans, PM2.5 levels over India have not noticeably reduced. PM2.5-associated health burdens in India have increased significantly in past decades. A fine resolution (0·01° × 0·01°) analysis of PM2.5-attribulable premature deaths (rather than the coarse-level analysis) may elucidate the reason for this increase and inform and effective start-of-the-art state-level and national emission control strategies. This study quantified the spatiotemporal dynamics of PM2.5-attributable premature deaths from 2001 to 2020 and applied a decomposition analysis to dissect the contribution of various associated parameters, such as PM2.5 concentration, population distribution and disease-specific baseline death rate. Results show significant spatiotemporal variations of PM2.5 and associated health burden in India. During the study period, population weighted PM2.5 value increased from 46.0 to 59.5 μg/m3 and associated non-communicable death increased around 87.6 %, from 1050 [95 % (CI): 880–1210] thousand to 1970 (95 % CI: 1658-2259) thousand. The states of Uttar Pradesh, Bihar, West Bengal, Maharashtra, Rajasthan, and Madhya Pradesh had the highest PM2.5-attributable deaths. In these states, non-accidental deaths increased from 232.1, 112.7, 81.4, 79.1, 66.3 and 58.5 thousand in 2001 to 424.1, 226.7, 156.2, 154.5, 123.3 and 119.7 thousand in 2020. In per capita population (/105 population), the highest PM2.5-attributable deaths were observed in Delhi, Uttar Pradesh, Bihar, Haryana and Punjab. Throughout the study period, demographic changes outweighed the health burden and were responsible for ~62.8 % increase of PM2.5-related non-accidental deaths across India, whereas the change in PM2.5 concentration influenced only 18.7 %. The change in baseline mortality rate impacts differently for the estimation of disease-specific mortality changes. Our findings suggest more dynamic and comprehensive policies at state-specific level, especially for North India is very indispensable for the overall decrease of PM2.5-related deaths in India.

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