Uncertainties in Emissions Estimates of Greenhouse Gases and Air Pollutants in China and India and Their Impacts on Regional Air Quality

Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in both China and India, leading to worsening air quality in Asia. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions inventories and quantification of their uncertainties is essential for better understanding of the linkages among emissions and air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO₂), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen oxides (NO_x), and particulate matter (PM) emission estimates from four source sectors for China and India. We focus on the period between 2000 and 2008 and in addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and assessed differences in the existing emissions estimates within each of the subnational regions. We found that large disagreements exist among the existing inventories at disaggregated levels. We further assessed the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plain and in the East and Central regions in China, where not only the emissions differences are high but also the simulated concentrations using different inventories. Our study also highlights the importance of constraining SO₂, NO_x, and NH₃ emissions for secondary PM concentrations.