the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
New insight into the formation and aging processes of organic aerosol from positive matrix factorization (PMF) analysis of ambient FIGAERO-CIMS thermograms
Abstract. Secondary organic aerosol (SOA) is an important component of organic aerosol (OA), yet its evolution of volatility remains unclear. We investigated SOA volatility at a downwind site of the Pearl River Delta (PRD) region in the fall of 2019, using a time-of-flight chemical ionization mass spectrometer coupled with a Filter Inlet for Gases and Aerosol (FIGAERO-CIMS). Positive matrix factorization (PMF) analysis was performed on the thermogram data of organic compounds measured by the FIGAERO-CIMS. Eight factors were resolved, including six daytime chemistry related factors, a biomass burning related factor (BB-LVOA, 10 %), and a nighttime chemistry related factor (Night-LVOA, 15 %) along with their corresponding volatility. Day-HNOx-LVOA (12 %) and Day-LNOx-LVOA (11 %) were mainly formed through gas-particle partitioning, with higher NOx promoting more volatile OA. Two aged OA factors (Day-aged-LVOA, 16 %; Day-aged-ELVOA, 11 %) reflected daytime photochemical aging, while Day-urban-LVOA (16 %) and Day-urban-ELVOA (7 %) were linked to urban plumes. Results show that both gas-particle partitioning (36 %) and photochemical aging (30 %) accounted for a major fraction in the afternoon during the urban air masses period, especially for high-NOx-like pathway (~21 %). In general, the six daytime OA factors collectively explain the majority (82 %) of daytime SOA identified by an aerosol mass spectrometer (AMS), while the highly oxygenated OA and hydrocarbon-like OA cannot be identified with FIGAERO-CIMS in this study. In summary, our results show that the volatility of OA is strongly governed by its formation pathways and subsequent atmospheric aging processes.
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Status: open (until 16 Nov 2025)
- RC1: 'Comment on egusphere-2025-4597', Anonymous Referee #1, 21 Oct 2025 reply
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The paper provides a comprehensive analysis of SOA formation and aging processes in the PRD region, using advanced measurements from a FIGAERO-CIMS coupled with PMF analysis. The study identifies and characterizes different SOA factors based on their volatility and formation pathways. The results highlight the significant role of gas-particle partitioning and photochemical aging in SOA formation, with variations driven by environmental factors such as NOx levels. The authors also compare these findings with data from AMS and discuss the limitations of FIGAERO-CIMS in detecting certain OA components. This manuscript is suitable for publication in ACP and I recommend it for publication after the following comments have been addressed.