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• We build a satellite-driven machine learning model to predict particulate sulfate concentrations across China using atmospheric big data from 2005 to 2018. • Our daily and monthly mean sulfate predictions agree well with ground observations with an out-of-bag cross-validation R2 of 0.68 and 0.93, respectively. • Population-weighted national annual mean sulfate concertation was relatively stable before the enforcement of the Air Pollution Prevention and Control Action Plan in 2013, then significantly decreased by 28.7% from 2013 to 2018. • The national annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7% and 42.3% from 2013 to 2018, respectively. Ambient fine particulate matter (PM 2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM 2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM 2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validation R2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m−3. But the sulfate level dramatically decreased to 7.7 µg m−3 in 2018, with a change rate of −28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate. [ABSTRACT FROM AUTHOR]