Long term variation of microphysical properties of black carbon in Beijing derived from observation and machine learning

Abstract The microphysical properties of black carbon (BC) importantly determine its absorption and hygroscopic properties. However this long-term information is difficult to obtain from field. In this study, the BC properties including the mass concentration, the coating volume ratio (VR) relative to refractory BC (rBC), the rBC diameter and the fraction of cloud condensation nuclei (CCN), are derived from a number of field experiments by a random forest model. This model effectively derives the long-term BC microphysical properties in Beijing region from 2013 to 2020 using continuous measurements of particulate matter (PM), gas, BC mass concentration and the meteorological parameters. The results reveal notably higher BC coatings (mean VR = 7.2) and a greater fraction of CCN-like BC (51%) in winter compared to other seasons. Following the implementation of national air pollution control measures in 2017, BC mass exhibited a substantial reduction of 60% (29%) in winter (summer), and VR decreased by 45% (24%). Apart from the influence of meteorological variations, these can be attributed to the declined primary emissions and the gas precursors which are associated with secondary formation of BC coatings. The reductions of both BC mass loading and coatings lead to its solar absorption decreased by 50%, and the fraction of CCN-like BC (likely in clouds) decreased by 23%. The environmental regulation will therefore continue reducing both direct and indirect radiative impacts of BC in this region.