Evolution and chemical characteristics of organic aerosols during wintertime PM2.5 episodes in Shanghai, China: Insights gained from online measurements of organic molecular markers
Abstract. Organic aerosol (OA) is a significant part of urban fine particulate matter (PM2.5) and a lack of detailed knowledge of their sources has increasingly hindered the improvement of air quality in China in recent years as significant reductions have been achieved in inorganic ion constituents. In this study, a wide range of organic molecular markers in PM2.5 were monitored with a bihourly time resolution using a Thermal desorption Aerosol Gas chromatograph system (TAG) in urban Shanghai in winter 2019. The molecular marker data have provided a unique source tracking ability in characterizing the evolution of organic aerosols during nine wintertime episodic events. Episodes primarily influenced by local air masses were characterized with higher proportions and mass increments of secondary OA. Rapid elevation in both absolute mass concentration and relative proportion was observed for primary and secondary OA markers indicative of vehicle emissions (e.g., alkanes, hopanes, and 2,3-dihydroxy-4-oxopentanoic acid), as well as cooking activities (e.g., saturated and unsaturated fatty acids, and C9 acids). In comparison, episodes under significant influences of transported air mass were typically associated with a predominant PM2.5 contribution from secondary inorganic aerosols and enhanced OA contribution from biomass burning activities. The latter was evident from the tracer data (e.g., levoglucosan, aromatic polycarboxylic acids, and nitro-aromatic compounds). Secondary OA markers associated with later generation products of hydrocarbon oxidation process, such as C3–5 dicarboxylic acids, were the most deficient during local episodes while notably enhanced during the episodes under influence of transported air masses, reflecting different extent and pathways of atmospheric aging processing. The ability of distinguishing the variations of OA evolution during different types of episodes demonstrates the value of online organic molecular measurements to episodic analysis. The results indicate that control of local urban sources such as vehicular and cooking emissions would lessen severity of local episodes while regional control of precursors for secondary inorganic aerosols and biomass burning activities would reduce PM2.5 episodes under synoptic conditions conducive for regional transport.
Shuhui Zhu et al.
Status: final response (author comments only)
RC1: 'Comment on acp-2022-813', Anonymous Referee #1, 03 Mar 2023
- AC1: 'Reply on RC1', Jian Zhen Yu, 27 Mar 2023
RC2: 'Comment on acp-2022-813', Anonymous Referee #2, 04 Apr 2023
- AC2: 'Reply on RC2', Jian Zhen Yu, 17 Apr 2023
RC3: 'Comment on acp-2022-813', Anonymous Referee #3, 22 Apr 2023
- AC3: 'Reply on RC3', Jian Zhen Yu, 09 May 2023
Shuhui Zhu et al.
Shuhui Zhu et al.
Viewed (geographical distribution)
The manuscript prepared by Zhu et al titled “Evolution and chemical characteristics of organic aerosols during wintertime PM2.5 episodes in Shanghai, China: Insights gained from online measurements of organic molecular markers” reported an online bi-hourly molecular tracer dataset collected by Thermal desorption Aerosol Gas chromatography system (TAG) in winter 2019, Shanghai. Combining with analytical results from other online instruments such as AMS and MARGA, the authors analyzed molecular markers (levoglucosan, C3-5 organic acids, C9 acids, DHOPA, phthalic acid, uFAs, sFAs etc.) in 9 episodes during their observation and found that vehicle and cooking emission were the two local sources for fine particulate matter while biomass burning was the main OA source contributed via regional transportation. Their results indicated that control of local urban sources such as vehicular, cooking, and biomass burning emissions would help alleviating the winter haze episodes in Shanghai. The paper is well prepared, but I found some of the conclusions are contradictory with each other and the current version lacks novelty in general out of a scientific perspective. The overall language needs to be improved. I sincerely hope the authors explain the following major concerns before the manuscript could be published.
1. Can the authors explain more about why they picked 2019 winter as astudying period for investigating the OA composition and evolution in Shanghai. How representative it is? Will the final conclusion of this work about the importance of control primary emissions such as cooking, vehicle, and biomass burning emissions change if the author changed the year of study?
2. Section 3.1: The authors analyzed 9 episodes in total and divided them into three categories, namely, transport episodes, local episodes, and mixed-influence episodes, but in Line 154-155 the author stated that the haze episodes were under the impacts from local emission and clean episodes were influenced by long range transportation of air mass. Such claims also seem contradictory to the following statement in Line 159-161, where the author again mentioned that episodes with high average PM2.5 level were found during transport episodes. The definitions and explanations for each types of episode should definitely be clearer in this section.
3. OC/EC method was used by the authors for SOM and POM estimation. Can the authors add uncertainty analysis for the SOM and POM estimations in this study? SOM as well as a variety of primary emissions were found to be dominant in the local episodes. Was the SOM partially influenced by primary emissions since primary factors were commonly strong during the local episodes? How accurate the estimation of SOM can be in this study?
4. C9 produced from ozonolysis of fatty acids were not detected to increase in their mass content during the local episode and the author then explain this was because of the low O3 mixing ratio. Did the author just mentioned the local episode was largely influenced by SOA formation based on Figure 2? Does this mean that most of SOA in the local episodes were formed form pathways other than ozonolysis, can the authors provide further evidence for this point?
5. From discussions of Figure 2, the authors claimed that the local episodes were significantly influenced by SOA. But in line 268, the author mentioned that AMS data indicated higher MO-OOA and LO-OOA were observed for the mixed-influence and transport episodes, indicating that OA in these two episodes were more aged. Should there at least be some assumptions given in the manuscript on how the PM1 data from AMS and the PM2.5 data from TAG were compared? The logic in terms of which episode underwent more profound secondary OA formation process is a bit mess in the current manuscript. The authors should be more explicit on which episode is more aged and has a higher formation of SOA under which specific conditions.
6. The hC4/C4 ratio was used as an indicator for aqueous phase secondary OH oxidation. However, as indicated in Figure 6e, the positive correlation between hC4/C4 and RH was found to be more significant for the non-episodic period compared to the episodic period. I’m afraid the explanation of impact from marine aerosol should not be persuasive as hC4 should be secondary formed according to the statement of the authors. More discussion needed to explain why the hC4/C4 ratio climbed up more significantly with the increase of RH during the non-episodic period.
Line 41: sentence needs to be rephrased
Line 54-56: references needed here
Line 58-60: This sentence is hard to understand. Please provide evidence in more detail
Line 67: while studying evolution processes…
Line 105: it is very abrupt to bring up residual oil combustion here
Line 180: SOA has already been defined previously no need to have SOM here
Line 184: SIA has already been defined
Line 224: what does “sizable” mean
Line 226-227: should be local episode with high SOM contribution that have high secondary molecular tracers?
Line 296-298: I am not sure if it is appropriate to just simply define aromatic SOA compounds into these two categories---they might have overlapped zones
Line 397: oxidation degree