Characterizing highly oxygenated organic molecules in limonene secondary organic aerosols: roles of temperature and relative humidity

Abstract

Highly oxygenated organic molecules (HOMs) are significant contributors to the formation of secondary organic aerosols (SOAs) and new particles in the atmosphere. The process of HOM formation via autoxidation is highly dependent on several factors, such as temperature, relative humidity (RH), and initial ozone concentration, among others. The current work investigates how temperature and RH affect the formation of HOMs in SOAs from limonene ozonolysis. Experiments were conducted in a laminar flow tube reactor under different experimental conditions (T = 5 °C and 25 °C; RH = 15% and 75%). A scanning mobility particle sizer was used to measure the concentration and size distribution of generated SOA particles. Fourier transform ion cyclotron resonance mass spectrometry was used to detect and characterize HOMs and SOAs. Experimental results show that lower temperatures (i.e., T = 5 °C) and higher RH levels (e.g., RH = 75%) promote the generation of HOMs and SOAs. Limonene-oxidation-derived HOMs exhibit a preference for stabilization under low-temperature and high-RH conditions. Within this context, semi-volatile, low-volatile, and extremely low-volatile organic compounds play a significant role. Our experimental findings indicate that the formation of C₁₀ compounds during limonene ozonolysis is strongly influenced by peroxy radical chemistry. Given that peroxy radicals are key intermediates in this process, their reactions—including autoxidation and bimolecular termination pathways—likely play a significant role in the formation and stabilization of HOMs in SOAs. The observed product distributions also suggest that these radicals contribute to the incorporation of multiple oxygen atoms, facilitating the formation of ELVOCs and LVOCs that ultimately drive particle-phase growth. The present work can improve our understanding of the generation of biogenic HOMs and SOAs at different temperatures and RH, which can be used in future exposure risk or climate models to provide more accurate air quality prediction and management.