Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Abstract

Fine particulate matter (PM2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78–1.26) million deaths in South Asia attributable to ambient PM2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%–39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM2.5 (>95 μg/m3). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54–0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Drivers of PM2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

“…Color shading in airsheds of significant exceedance (40-80 μg/m 3 ) is in shades of orange and red, while that in airsheds of extreme exceedance (80-140 μg/m 3 ), is in maroon and brown. Consistent with recent studies (Chatterjee et al, 2023;, extreme exceedance of PM 2.5 annual standard occurs in a broad airshed across the entire IGP from Punjab in the west-to-West Bengal and Sikkim in the east. Airsheds with PM 2.5 hotspots of annual mean concentrations between 110 and 140 μg/m 3 lie in Bihar, Uttar Pradesh and Punjab.…”

Unequal Health Risks and Attributable Mortality Burden of Source-Specific PM2.5 in China

“…Downscaling techniques in prior studies were predominantly utilized to enhance the resolution of data sets, primarily focusing on the total mass concentration of PM 2.5 . , In contrast, the widely used inverse distance weighted (IDW) interpolation method was employed to downscale both the total and source-specific PM 2.5 concentrations derived from CMAQ simulations in this study, aiming to achieve a finer grid resolution of 0.1° × 0.1° (approximately 10 × 10 km 2 ). − Subsequently, the proportions of the downscaled daily average concentrations of source-specific PM 2.5 to the total PM 2.5 mass for each grid were determined. The Tracking Air Pollution (TAP) in China database was utilized to generate an adjusted and downscaled data set at a spatial resolution of 0.1° × 0.1° (approximately 10 × 10 km 2 ).…”

Air pollution and lung cancer

“…Potential long-lasting detrimental effects from exposure to air pollutants during infancy or childhood resulting in the development of mutant clones should be considered in future studies. In addition, as discussed above [23][24][25][26][27][28][29][30][31][32][33] , PM 2.5 is comprised of a complex mixture of chemical species from diverse sources [23][24][25][26][27][28][29][30][31][32][33]77,78 , each potentially having different effects on lung carcinogenesis. Global spatial variation in PM 2.5 composition may explain the differences in the molecular alterations in lung adenocarcinoma between countries 79 .…”