Response to reviewers for the paper “ Aging impact on sources, volatility, and viscosity of organic aerosols in the Chinese outflows ”

To investigate the aging impact on sources, volatility, and viscosity of organic aerosols (OA) in the Chinese outflows, a high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) coupled with a thermodenuder (TD) was deployed in the spring of 2018 in Dongying, which is a regional receptor site of metropolitan emissions in North China Plain (NCP). The average mass concentration of PM 1 was 31.5 ± 22.7 μ g m –3 , which was mainly composed of nitrate (33 %) and 30 OA (25 %). The source apportionment results show the OA was mainly contributed by oxygenated OA (OOA) from secondary sources, including background-OOA (33 %) representing a background concentration of OA (2.6 μ g m –3 ) in the NCP area, and transported-OOA (33 %) oxidizing from urban emissions. The other two factors include aged hydrocarbon-liked OA (aged-HOA, 28 %) from transported vehicle emissions and biomass burning OA (BBOA, 5 %) from local open burnings. The volatility of total OA (average C* = 3.2×10 –4 µg m –3 ) i n this study is generally lower than those in previous 35 field studies, which is mainly due to the high OA oxidation level resulting from aging processes during transport. The volatilities of OA factors follow the order of background-OOA (average C* = 2.7×10 –5 μ g m –3 ) < transported-OOA (3.7×10 –4 μ g m –3 ) < aged-HOA (8.1×10 –4 μ g m –3 ) < BBOA (0.012 μ g m –3 ), indicating the probable existence of oligomers. The viscosity estimation suggests that the majority of ambient OA in this study behaves as semi-solid (60 %), liquifies at higher RH (21 %), and solidifies (19 %) during noon time when the RH is low and the oxidation level is high. Finally, the estimated 40 mixing time of OA varies dramatically from minutes at night to years in the afternoon, emphasizing the necessity to consider its dynamic kinetic limits when modeling OA. In general, the overall results of this study improve the understanding of the aging impact on OA volatility and viscosity. different types of organic species, was moderately volatile in this study, where nitrate was the most volatile species and sulfate was the least. Ambient inorganic aerosols all showed higher residuals upon heating at higher TD temperatures than their laboratory-derived pure standards, indicating the universal existence of low volatile metallic or organic-related species in ambient aerosols. This supports the complexity of ambient aerosols. Source apportionment of OA resolved four OA factors, BBOA (5 %), aged-HOA (28 %), transported-OOA (33 %), and background-OOA (33 %). BBOA, which was considered as emitted from the open fire nearby, is the most volatile in this study (average C* = 0.012 μ g m –3 ). Aged-HOA was characterized by high proportions of C x H y+ ions and had good correlations with primary VOC species (benzene and ethyl toluene), as well as a pronounced peak of diurnal variations in the morning, suggesting that it is mainly transported from vehicle emissions from surrounding towns. The volatility of aged-HOA was impacted by the aging process, which has lower volatility (average C* = 8.1×10 –4 μ g m –3 ) than those of urban areas in NCP (Beijing), however still shows high SOA formation potential. In this study, total OOA (transported-OOA + background-OOA) accounted for the largest fractions of the OA (66 %) due to long-distance aging and fewer effects from local emissions than those of urban areas. Generally, transported-OOA (average C* = 3.7×10 μ g m –3 ) showed good agreements with secondary inorganic species, supporting their similar origins. Background-OOA showed the background concentration of OA in the outflow of the Chinese continent, which was around 2.6 µg m –3 on average. The background-OA was the least volatile factor in this study (average C* = 2.7×10 –5 μ g m –3 ), implying the existence of a large fraction of oligomers in this type of SOA and shall be further investigated. The results suggest the aging processes during the transport of air plumes can significantly enhance the SOA formation data. laboratory experiment on volatility. OA source analysis. the viscosity analysis.