the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Aging impact on sources, volatility, and viscosity of organic aerosols in the Chinese outflows
- 1State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- 2CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
- 3Chinese Academy of Sciences University, Beijing 100049, China
- 4Guangdong-Hong Kong-Macao, Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China
- 5Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou 510640, China
- 6Shanghai Academy of Environmental Sciences, Shanghai 200233, China
- 7Tai’an Environmental Protection Bureau, Tai’an, Shandong 271000, China
- 8Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- 9Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
- 10Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, China
- 11School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
- 12Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
- 13Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
- anow at: School of Ecology and Environment, Anhui Normal University, Wuhu, Anhui 241000, China
- These authors contributed equally to this work.
- 1State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- 2CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
- 3Chinese Academy of Sciences University, Beijing 100049, China
- 4Guangdong-Hong Kong-Macao, Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China
- 5Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou 510640, China
- 6Shanghai Academy of Environmental Sciences, Shanghai 200233, China
- 7Tai’an Environmental Protection Bureau, Tai’an, Shandong 271000, China
- 8Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- 9Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
- 10Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, China
- 11School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
- 12Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
- 13Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
- anow at: School of Ecology and Environment, Anhui Normal University, Wuhu, Anhui 241000, China
- These authors contributed equally to this work.
Abstract. 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 PM1 was 31.5 ± 22.7 μg m–3, which was mainly composed of nitrate (33 %) and 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 μg 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) in this study is generally lower than those in previous 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 μg m–3) < transported-OOA (3.7×10–4 μg m–3) < aged-HOA (8.1×10–4 μg m–3) < BBOA (0.012 μg 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 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.
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Journal article(s) based on this preprint
Tingting Feng et al.
Interactive discussion
Status: closed
-
RC1: 'Comment on acp-2022-575', Anonymous Referee #2, 15 Sep 2022
General comments:
The manuscript by Tingting Feng et al. investigated the aging impact on sources, volatility, and viscosity of organic aerosols in Dongying. They found that the BBOA was the most volatile OA factor, followed by aged-HOA, transported-OOA and background-OOA. In addition, the estimated mixing time of OA varied dramatically from minutes at night to years in the afternoon, emphasizing the necessity to consider its dynamic kinetic limits when modeling OA. The topic fits well within the scope of Atmospheric Chemistry and Physics. This manuscript is generally well written. Before its publication, the following comments need to be addressed.
Specific Comments:
1 More information needs to be provided to support source apportionment results in the background-OOA and transported-OOA. For example, the background-OOA did show a relative flat diurnal variation. However, the elevated loading of background-OOA was occurred after excluding the impacts of PBL. In addition, the lower O/C of transported-OOA compared to background-OOA was observed. Is such difference in the oxidation state one of the reasons that you name background-OOA and transported-OOA? If so, please list the references and explain the reasons. In addition, is there any other evidences to support that factor 2 is related to the ageing of HOA (rather than COA, CCOA or other primary emissions)? What about the correlations of aged-HOA profiles in this study with the aged traffic emissions in laboratory studies?
2 Are there any specific reasons for using a constant CE (0.5), rather than CDCE? How about the neutralization in ambient air and each TD temperature? Please mention it here.
3 How did you measure the organic nitrate? Did you exclude the impacts of organic nitrates on the measured/predicated NH4 in Fig. 6(f). I am also curious the lower mass concentrations of organic nitrate in the polluted periods compared to entire periods. Please elaborate.
4 The discussion regarding oligomers should be backed by the evidence rather than speculated upon at all throughout the manuscript.
5 Did you assess how long it takes to reach stability after switching? In my viewpoint, there might be a significant uncertainty using the switched time of 4 min. The authors need to address such uncertainties in the revised manuscript.
6 Are there any other metal containing constituents measurements to support your assumptions (e.g., line 365-367)? Looking into the HR data(e.g., Na+ , K+ and Pb+ ) would be helpful.
7 The author have not discussed the inlet used for dilution fully. An experimental design for dilution needs to be included in Section 2. In addition, a discussion about the additional mass losses of four OA factors as functions of the dilution factor is irrelevant for the section 3.4.2.
8 Line 116: Inaccurate "PM1". Do you mean "NR-PM1"?
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RC2: 'Comment on acp-2022-575', Anonymous Referee #1, 24 Sep 2022
Quantifications of the physicochemical properties, particularly volatility and viscosity, of OA are vital to understanding its environmental and climate effects. Feng et al. deployed HR-AMS coupled with a TD to investigate the aging impact on sources, volatility, and viscosity of OA in a regional receptor site of metropolitan emissions in North China Plain. They find that the volatility of OA in this receptor site is generally lower than those in previous field studies, indicating the large impact of atmospheric aging on the OA oxidation levels during transport. As well, the phase state of ambient OA is investigated from the estimated viscosity. The results have important implications for the understanding of the aging impact on OA volatility and viscosity. The methods are solid and the manuscript is well written. It can be recommended for publication after addressing the following minor comments.
Specific comments:
Section 2.2.1 HR-ToF-AMS: Which mode is the AMS running at? Only V mode? What’s the time resolution?
Lines 159-163: I would suggest describing a bit more details on why four factors were chosen, in particular, one aged-HOA factor was chosen instead of two HOA factors in this study.
Line 173: The sampling flow was switched between TD and bypass every 4 min while the time resolution of SMPS measurement is 5 min. Will this lead to a mixed bypass and TD sample for each measurement of SMPS? Please clarify.
Lines 295-299: It is surprising that the O:C of aged-HOA can be that large during transport from surrounding urban areas. How long would it take for the vehicle emissions transport to this site? Is it possible that HOA undergoes aqueous oxidation and leads to a large increase of the O:C?
Lines 438-440: Is there any other evidence that oligomers are formed? For example, is there a significant increase of the larger ions (m/z > 150) in the AMS spectra?
Lines 454-455: Can the authors provide more details on how the dilution is performed?
Technical comments:
Line 205: The font of the website is inconsistent with the main text.
- AC1: 'Comment on acp-2022-575', Weiwei Hu, 15 Nov 2022
Peer review completion
Post-review adjustments
Interactive discussion
Status: closed
-
RC1: 'Comment on acp-2022-575', Anonymous Referee #2, 15 Sep 2022
General comments:
The manuscript by Tingting Feng et al. investigated the aging impact on sources, volatility, and viscosity of organic aerosols in Dongying. They found that the BBOA was the most volatile OA factor, followed by aged-HOA, transported-OOA and background-OOA. In addition, the estimated mixing time of OA varied dramatically from minutes at night to years in the afternoon, emphasizing the necessity to consider its dynamic kinetic limits when modeling OA. The topic fits well within the scope of Atmospheric Chemistry and Physics. This manuscript is generally well written. Before its publication, the following comments need to be addressed.
Specific Comments:
1 More information needs to be provided to support source apportionment results in the background-OOA and transported-OOA. For example, the background-OOA did show a relative flat diurnal variation. However, the elevated loading of background-OOA was occurred after excluding the impacts of PBL. In addition, the lower O/C of transported-OOA compared to background-OOA was observed. Is such difference in the oxidation state one of the reasons that you name background-OOA and transported-OOA? If so, please list the references and explain the reasons. In addition, is there any other evidences to support that factor 2 is related to the ageing of HOA (rather than COA, CCOA or other primary emissions)? What about the correlations of aged-HOA profiles in this study with the aged traffic emissions in laboratory studies?
2 Are there any specific reasons for using a constant CE (0.5), rather than CDCE? How about the neutralization in ambient air and each TD temperature? Please mention it here.
3 How did you measure the organic nitrate? Did you exclude the impacts of organic nitrates on the measured/predicated NH4 in Fig. 6(f). I am also curious the lower mass concentrations of organic nitrate in the polluted periods compared to entire periods. Please elaborate.
4 The discussion regarding oligomers should be backed by the evidence rather than speculated upon at all throughout the manuscript.
5 Did you assess how long it takes to reach stability after switching? In my viewpoint, there might be a significant uncertainty using the switched time of 4 min. The authors need to address such uncertainties in the revised manuscript.
6 Are there any other metal containing constituents measurements to support your assumptions (e.g., line 365-367)? Looking into the HR data(e.g., Na+ , K+ and Pb+ ) would be helpful.
7 The author have not discussed the inlet used for dilution fully. An experimental design for dilution needs to be included in Section 2. In addition, a discussion about the additional mass losses of four OA factors as functions of the dilution factor is irrelevant for the section 3.4.2.
8 Line 116: Inaccurate "PM1". Do you mean "NR-PM1"?
-
RC2: 'Comment on acp-2022-575', Anonymous Referee #1, 24 Sep 2022
Quantifications of the physicochemical properties, particularly volatility and viscosity, of OA are vital to understanding its environmental and climate effects. Feng et al. deployed HR-AMS coupled with a TD to investigate the aging impact on sources, volatility, and viscosity of OA in a regional receptor site of metropolitan emissions in North China Plain. They find that the volatility of OA in this receptor site is generally lower than those in previous field studies, indicating the large impact of atmospheric aging on the OA oxidation levels during transport. As well, the phase state of ambient OA is investigated from the estimated viscosity. The results have important implications for the understanding of the aging impact on OA volatility and viscosity. The methods are solid and the manuscript is well written. It can be recommended for publication after addressing the following minor comments.
Specific comments:
Section 2.2.1 HR-ToF-AMS: Which mode is the AMS running at? Only V mode? What’s the time resolution?
Lines 159-163: I would suggest describing a bit more details on why four factors were chosen, in particular, one aged-HOA factor was chosen instead of two HOA factors in this study.
Line 173: The sampling flow was switched between TD and bypass every 4 min while the time resolution of SMPS measurement is 5 min. Will this lead to a mixed bypass and TD sample for each measurement of SMPS? Please clarify.
Lines 295-299: It is surprising that the O:C of aged-HOA can be that large during transport from surrounding urban areas. How long would it take for the vehicle emissions transport to this site? Is it possible that HOA undergoes aqueous oxidation and leads to a large increase of the O:C?
Lines 438-440: Is there any other evidence that oligomers are formed? For example, is there a significant increase of the larger ions (m/z > 150) in the AMS spectra?
Lines 454-455: Can the authors provide more details on how the dilution is performed?
Technical comments:
Line 205: The font of the website is inconsistent with the main text.
- AC1: 'Comment on acp-2022-575', Weiwei Hu, 15 Nov 2022
Peer review completion
Post-review adjustments
Journal article(s) based on this preprint
Tingting Feng et al.
Tingting Feng et al.
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