Nationwide Overestimation of Black Carbon Emissions During Clean Air Action Identified by Assimilation Inversion

Abstract

An accurate estimate of black carbon (BC) emission is critical, as BC represents one of the most important short-lived climate forcers. The widely used BC emission inventories were developed using either bottom-up or top-down approaches, both of which have large uncertainties. The challenges of the bottom-up approach include uncertainties in emission factors for different fuel types and combustion technologies. Conversely, top-down BC emission inversion relies primarily on satellite-retrieved aerosol absorption optical depth, which has significant limitations in quantifying BC-specific contributions. The China Atmospheric Monitoring Network, established by the China Meteorological Administration, provides ground-based hourly BC observations and a valuable opportunity to constrain BC emissions. This study presents the first application of these nationwide BC observations in emission inversion during the Clean Air Action (2013–2017), achieved using the 4DEnVar assimilation technique. Validation against independent observations demonstrates significant improvements in posterior estimates, reducing the root mean square error by 36.7%. Compared to the posterior, widely used bottom-up inventories (e.g., MEIC) overestimate China's total BC emissions by 36.7%, with overestimations ranging up to 80.6% in the North China Plain (averaged between 2013 and 2017). In terms of climate impact, MEIC-based estimates yield an 18.7% higher direct radiative effect on average, while CMIP6 historical estimates further exaggerate BC-induced forcing by a factor of 1.7. Additionally, our inversion reveals that annual total BC emissions declined markedly by 28.1% during the Clean Air Action, from 1.24 to 0.89 Tg. These findings are critical for quantifying the role of BC in the regional and global climate.