Mixing state and evolutionary mechanism of oxalic acid homologs in Liaocheng, East China: Insights from seasonal and hourly observations

Oxalic acid (C2) is a significant tracer of secondary organic aerosols (SOA), yet its precursors, evolutionary processes, and formation mechanisms are not fully understood. This knowledge gap leads to uncertainties in evaluating the climate effect and global budget of SOA. Here we compared the size distribution, mixing fraction, and evolutionary mechanism of C2-containing particles between summer and winter. In summer, the number of C2 particles and their homologs decreased compared to winter. However, the proportion of C2 relative to the total number of determined particles increased, indicating that the summertime particles are more aged. Higher relative aerosol acidity (Rra) and lower in-situ pH (pHis) in summer suggest that particles are more acidic during this season. Correlation analysis and temporal variation characteristics suggest that from 9: 00 to 15: 00 in summer, C2 particles mostly originate from the photochemical decomposition of larger dicarboxylic aids, driven by O3 concentration. Conversely, from 16: 00 to 20: 00, C2 particles are predominantly formed through aqueous-phase oxidation, influenced by higher relative humidity (RH), aerosol liquid water content (ALWC), and acidity. Additionally, heavy metal particles were the predominant type of C2 particles, and C2 particles exhibited an opposite diurnal variation to Fe in summer, suggesting that the photolysis of iron oxalate complexes is an important sink of C2 particles during this period. In winter, biomass burning (BB) particles were the most abundant, and a robust correlation between levoglucosan and C2 particles indicated a substantial influence of BB on C2 particles. The aqueous generation of C2 particles from a-dicarbonyls driven by acidity was most effective when RH varied from 40% to 60% in the wintertime state of particles. These findings highlight the hourly and seasonal variations in the sources and evolutionary processes of SOA. Such variations must be considered in developing control measures and simulating the climate effect of SOA. (c) 2024 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.