Abstract View
Using Observational Constraints to Improve Aerosol Pollution Attribution over India
SIDHANT J. PAI, Colette L. Heald, Hugh Coe, James Brooks, Mark W. Shephard, Enrico Dammers, Joshua S. Apte, Gan Luo, Fangqun Yu, Christopher D. Holmes, Chandra Venkataraman, Pankaj Sadavarte, Kushal Tibrewal, Massachusetts Institute of Technology
Abstract Number: 341
Working Group: Remote and Regional Atmospheric Aerosol
Abstract
The Indian subcontinent is subject to some of the highest levels of ambient air pollution in the world, with over 99% of the population living in areas that exceed the World Health Organization guidelines for fine particulate matter. Recent research has demonstrated that a significant fraction of the total aerosol burden is secondary in nature, making air pollution management a regional problem. Despite this, regional PM2.5 pollution models and associated health assessments in India are largely based on simulations that have not been evaluated rigorously against in situ measurements, primarily due to the historical dearth of such observations. Here, we demonstrate that, while bulk PM2.5 observations are somewhat well-simulated by the model, a comparison with airborne measurements highlights large biases in the ammonium and nitrate aerosol simulations. A comparison of five different emissions inventories over the region illustrates large spreads in emissions estimates, particularly for ammonia. We use satellite retrievals from the CrIS and TROPOMI instruments to constrain model emissions of NH3 and NOx and incorporate process-level changes to improve the model. The resulting simulation demonstrates significantly lower bias when validated against speciated airborne aerosol measurements, particularly for nitrate and ammonium aerosol. Using the observationally validated simulation, we estimate that fine aerosol pollution accounts for approximately 1.4 million annual premature deaths in India. While no single emissions sector is paramount, the RCO (residential, commercial and other) and energy sectors contribute the most (24% and 21% respectively) to populated-weighted PM2.5 exposure across India, with important regional heterogeneity. Significant differences in source attributions between the Base and Modified simulations highlight the urgent need for speciated aerosol observational constraints at the surface and in the free troposphere to provide more accurate aerosol compositional information, improve the regional modelling of fine particulate, and enable informed air-quality management decisions.