Sources and composition of elemental carbon during haze events in North China by a high time-resolved study

Abstract

Despite the implementation of stringent emission reduction measures in the past year, severe winter haze events still occurred frequently in North China, with only marginal decreases observed in elemental carbon (EC) concentrations. EC not only constitutes a fraction of particle mass but also interacts with boundary layer and influences haze formation. Given the complex composition of EC, characterizing its sources and composition during haze processes is challenging yet crucial for understanding haze formation and evolution. Here, hourly-resolution PM2.5 samples were collected during three different haze event (P1-P3) in the North China Plain to investigate dynamic changes in EC source across different haze processes. The average EC concentrations and char/soot ratios were 9.94 ± 4.80 μgC·m−3, 14.5 ± 6.93 μgC·m−3, 15.9 ± 5.54 μgC·m−3, and 2.42 ± 0.98, 2.70 ± 0.88, 2.61 ± 0.95 for P1, P2 and P3, respectively. Backward trajectory analysis showed distinct variations in EC concentration and composition under the influence of different air masses during the three haze events, with local air masses influenced days exhibiting higher EC concentrations and char/soot ratios. The char/soot ratio based diagnostic method suggested that EC was predominantly influenced by coal combustion and vehicle emissions. Further positive matrix factorization analysis suggested that biomass burning and residential coal combustion were the main contributors of EC (58 %) and played a dominant role in driving variations in EC concentrations during haze episodes. Potential source contribution function analysis results highlight that local biomass burning and residential coal combustion could be major reason for the EC elevation in different haze events. Our results provide valuable insights into the sources and composition of EC during haze events, facilitating the implementation of effective measures for mitigating both EC and PM pollution.