the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report: Ambient volatile organic compounds (VOCs) pollution at urban Beijing: characteristics, sources, and implications for pollution control
- 1State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- 2State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
- 1State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- 2State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Abstract. The increasing ozone (O3) pollution and high fraction of secondary organic aerosols (SOA) in fine particle mass highlighted the importance of volatile organic compounds (VOCs) in air pollution control. In this work, a campaign of comprehensive field observations was conducted at an urban site in Beijing, from December 2018 to November 2019, to identify the composition, sources, and secondary transformation potential of VOCs. The total mixing ratio of the 95 quantified VOCs (TVOC) observed in this study ranged from 5.5–118.7 ppbv with the mean value of 34.9 ppbv, and the contemporaneous mixing ratios of TVOC was significantly lower than those observed in 2014 and 2016, confirming the effectiveness of VOCs emission control measures in Beijing in recent years. Alkanes, OVOCs and halocarbons were the dominant chemical groups, accounting for 75–81 % of the TVOCs across the sampling months. High and low-O3/PM2.5 months as well as several O3/PM2.5 polluted days were identified during the sampling period. By deweathered calculation, we found that high O3/PM2.5 levels were due to both enhanced precursor emission levels and meteorological conditions favorable to O3 and PM2.5 production. The molar ratios of VOCs to NOX indicated that O3 formation was limited by VOCs during the whole sampling period. Diesel exhaust and industrial emission were identified as the major VOCs sources on both O3-polluted and PM2.5-polluted days based on positive matrix factorization (PMF) analysis, accounting for 46 % and 53 %, respectively. Moreover, higher proportion of oil/gas evaporation was observed on O3-polluted days (18 %) than that on O3-clean days (13 %), and higher proportion of coal/biomass combustion was observed on PM2.5-polluted days (18 %) than that on PM2.5-clean days (13 %). On the base of O3 formation impact, VOCs from fuel evaporation and diesel exhaust particularly toluene, xylenes, trans-2-butene, acrolein, methyl methacrylate, vinyl acetate, 1-butene and 1-hexene were the main contributors, illustrating the necessity of conducting emission controls on these pollution sources and species for alleviating O3 pollution. Instead, VOCs from diesel exhaust and coal/biomass combustion were found to be the dominant contributors for secondary organic aerosol formation potential (SOAFP), particularly the VOC species of toluene, 1-hexene, xylenes, ethylbenzene and styrene, and top priority should be given to these for the alleviation of haze pollution. The positive matrix factorization (PSCF) analysis showed that O3 and PM2.5 pollution was mainly affected by local emissions. This study provides insights for government to formulate effective VOCs control measures for air pollution in Beijing.
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Lulu Cui et al.
Status: closed
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RC1: 'Comment on acp-2021-959', Anonymous Referee #1, 17 Jan 2022
Cui et al. conducted a campaign of comprehensive field observations at an urban site in Beijing. The composition, sources, and secondary transformation potential of VOCs were also identified. Overall, the study is very interesting and shows some new findings. However, the manuscript still suffers from many flaws especially the language expression. Furthermore, section 3.2.1 is not well-organized and needs major revisions. The detailed comments are as follows:
- Why not perform the hourly measurement of VOCs? To the best of my knowledge, the daily resolution for VOCs measurement is too coarse. Especially, the PMF model needs substantial observation data, which ensures the model’s reliability.
- The authors need to add the detailed QA/QC of VOCs and other criteria pollutants in section 2.1. The information is very important otherwise the study might be meaningless.
- Section 2.3: Why do you use RF model rather than other decision tree model or chemical transport model (CTM)? The predictive performance of RF model might be worse than GBDT and XGBoost. Meanwhile, CTM is a process-based model, which could clearly explain the contribution of many VOC species to O3 Moreover, the hyperparameter of RF model should be added.
- Section 2.4: The BS, DISP, and BS-DISP tests should be also added.
- Section 2.5: I think the PSCF analysis is not important in this study and could be removed.
- Section 3.2.1: Why not distinguish the meteorological and emission contributions to each VOC species?
- Section 3.3: The source identification method of each source based on VOC fingerprint should be added in this part. I think this part is too rough and should be rewritten.
- Conclusion is too long and should be shorten and reorganized.
- Data availability: I suggest the authors open the VOC dataset and it is very valuable to some researchers engaged in air quality modelling.
- The English throughout the manuscript should be significantly revised.
- AC1: 'Reply on RC1', Lulu Cui, 28 Mar 2022
-
RC2: 'Comment on acp-2021-959', Anonymous Referee #2, 05 Feb 2022
The research focused on ambient volatile organic compounds pollution at urban Beijing, and analyzed their characteristics, sources, and control effects. This study is of interest to the atmospheric scientists and suitable for the ACP. The observation data were detailed presented, the chemical composition and emission sources were analyzed aiming at different months and different O3- or PM2.5- pollution days, and the VOCs decline was found through comparing with reference results to support the control effects. However, I have a few concerns that should be addressed before the acceptance of the manuscript.
Major comments:
- In introduction section, the air pollution status has greatly changed in past several years in Beijing, due to the strict control measures implemented. However, the corresponding introductions were outdated and can’t present the current pollution characteristics. For example, line42 about SOA fraction in PM2.5, line 48 about SOA contribution to haze pollution, line 56 about the contribution of biogenic and anthropogenic sources, and so on. The recent references and their conclusions should be referred to.
- Methodology section, VOCs detection system should be GC-MS, but not GC (as mentioned in lines 95-96), for Agilent 5975 uses mass spectrometry detector. If the detector only included MSD but not included FID, C2 hydrocarbons would not be detected but they widely exist in atmosphere. This point should be illustrated. In addition, the efficiency of this analyze system for aldehydes should be well discussed. Because various monitoring standards don’t explicitly recommend the “canister sampling-GC/MS analyzer” to detect aldehydes.
- This study used the fact that O3 or PM2.5 pollution event happening to define high-O3 months (Apr, May, Jun, Jul and Sep) and high-PM2.5 months (April, May, Oct, Nov, Dec, Jan). It seems weird. For example, although O3 event never happened in Aug, but ozone level was also relatively higher in Aug than in Apr and Sep. So Aug should be considered as the high-O3 month, comparing with Apr and Sep. And then, in the results of PMF, the source apportionment in low-O3 months (Oct, Nov, Dec, Jan) was different with that in high-PM2.5 months (April, May, Oct, Nov, Dec, Jan), but similar to that in low-PM2.5 months (Jun, Jul and Aug). This conclusion was unreasonable to a certain extent.
- When using PSCF to explore the spatial potential sources of VOCs in urban Beijing, 24h was considered for all species. However, the lifetimes of various VOCs species were greatly different, several hours for alkenes, but several days for some alkanes and halocarbons. I suggest various groups of VOCs should be individually considered, to give the lifetime hours in backward trajectories.
Minor comments:
Abstract: “O3/PM2.5” frequently appeared but without an explicit definition. It is hard to understand the “high and low-O3/PM2.5 months”, “O3/PM2.5 polluted days”, and “high O3/PM2.5 levels”, etc.
Lines 32-34: “The positive matrix factorization (PSCF) analysis showed that O3 and PM2.5 pollution was mainly affected by local emissions. ” PSCF was conducted for VOCs, but not for ozone and PM2.5. No evidence to support this conclusion.
Line 47: VOCs chemistry in ozone formation involves gas-phase reaction, but not multiphase reaction.
Line 104: the “coefficient” should be coefficients; “was” should be “were”
Line 111-112: air pressure appeared twice.
More detailed model performance verifications (RF) are necessary, although R2 has provided in Fig. S2.
Line 191-193: I cannot figure out the sentence, suggesting checking out syntax rules.
Line 234: Fig. S3 was mentioned, however, there is not Fig. S3 in the supplement of this passage.
line 243-244: “Alkenes, aromatics and OVOCs were the three contributing chemical groups to O3 formation”, should be “the three biggest contributors”.
- AC2: 'Reply on RC2', Lulu Cui, 28 Mar 2022
Status: closed
-
RC1: 'Comment on acp-2021-959', Anonymous Referee #1, 17 Jan 2022
Cui et al. conducted a campaign of comprehensive field observations at an urban site in Beijing. The composition, sources, and secondary transformation potential of VOCs were also identified. Overall, the study is very interesting and shows some new findings. However, the manuscript still suffers from many flaws especially the language expression. Furthermore, section 3.2.1 is not well-organized and needs major revisions. The detailed comments are as follows:
- Why not perform the hourly measurement of VOCs? To the best of my knowledge, the daily resolution for VOCs measurement is too coarse. Especially, the PMF model needs substantial observation data, which ensures the model’s reliability.
- The authors need to add the detailed QA/QC of VOCs and other criteria pollutants in section 2.1. The information is very important otherwise the study might be meaningless.
- Section 2.3: Why do you use RF model rather than other decision tree model or chemical transport model (CTM)? The predictive performance of RF model might be worse than GBDT and XGBoost. Meanwhile, CTM is a process-based model, which could clearly explain the contribution of many VOC species to O3 Moreover, the hyperparameter of RF model should be added.
- Section 2.4: The BS, DISP, and BS-DISP tests should be also added.
- Section 2.5: I think the PSCF analysis is not important in this study and could be removed.
- Section 3.2.1: Why not distinguish the meteorological and emission contributions to each VOC species?
- Section 3.3: The source identification method of each source based on VOC fingerprint should be added in this part. I think this part is too rough and should be rewritten.
- Conclusion is too long and should be shorten and reorganized.
- Data availability: I suggest the authors open the VOC dataset and it is very valuable to some researchers engaged in air quality modelling.
- The English throughout the manuscript should be significantly revised.
- AC1: 'Reply on RC1', Lulu Cui, 28 Mar 2022
-
RC2: 'Comment on acp-2021-959', Anonymous Referee #2, 05 Feb 2022
The research focused on ambient volatile organic compounds pollution at urban Beijing, and analyzed their characteristics, sources, and control effects. This study is of interest to the atmospheric scientists and suitable for the ACP. The observation data were detailed presented, the chemical composition and emission sources were analyzed aiming at different months and different O3- or PM2.5- pollution days, and the VOCs decline was found through comparing with reference results to support the control effects. However, I have a few concerns that should be addressed before the acceptance of the manuscript.
Major comments:
- In introduction section, the air pollution status has greatly changed in past several years in Beijing, due to the strict control measures implemented. However, the corresponding introductions were outdated and can’t present the current pollution characteristics. For example, line42 about SOA fraction in PM2.5, line 48 about SOA contribution to haze pollution, line 56 about the contribution of biogenic and anthropogenic sources, and so on. The recent references and their conclusions should be referred to.
- Methodology section, VOCs detection system should be GC-MS, but not GC (as mentioned in lines 95-96), for Agilent 5975 uses mass spectrometry detector. If the detector only included MSD but not included FID, C2 hydrocarbons would not be detected but they widely exist in atmosphere. This point should be illustrated. In addition, the efficiency of this analyze system for aldehydes should be well discussed. Because various monitoring standards don’t explicitly recommend the “canister sampling-GC/MS analyzer” to detect aldehydes.
- This study used the fact that O3 or PM2.5 pollution event happening to define high-O3 months (Apr, May, Jun, Jul and Sep) and high-PM2.5 months (April, May, Oct, Nov, Dec, Jan). It seems weird. For example, although O3 event never happened in Aug, but ozone level was also relatively higher in Aug than in Apr and Sep. So Aug should be considered as the high-O3 month, comparing with Apr and Sep. And then, in the results of PMF, the source apportionment in low-O3 months (Oct, Nov, Dec, Jan) was different with that in high-PM2.5 months (April, May, Oct, Nov, Dec, Jan), but similar to that in low-PM2.5 months (Jun, Jul and Aug). This conclusion was unreasonable to a certain extent.
- When using PSCF to explore the spatial potential sources of VOCs in urban Beijing, 24h was considered for all species. However, the lifetimes of various VOCs species were greatly different, several hours for alkenes, but several days for some alkanes and halocarbons. I suggest various groups of VOCs should be individually considered, to give the lifetime hours in backward trajectories.
Minor comments:
Abstract: “O3/PM2.5” frequently appeared but without an explicit definition. It is hard to understand the “high and low-O3/PM2.5 months”, “O3/PM2.5 polluted days”, and “high O3/PM2.5 levels”, etc.
Lines 32-34: “The positive matrix factorization (PSCF) analysis showed that O3 and PM2.5 pollution was mainly affected by local emissions. ” PSCF was conducted for VOCs, but not for ozone and PM2.5. No evidence to support this conclusion.
Line 47: VOCs chemistry in ozone formation involves gas-phase reaction, but not multiphase reaction.
Line 104: the “coefficient” should be coefficients; “was” should be “were”
Line 111-112: air pressure appeared twice.
More detailed model performance verifications (RF) are necessary, although R2 has provided in Fig. S2.
Line 191-193: I cannot figure out the sentence, suggesting checking out syntax rules.
Line 234: Fig. S3 was mentioned, however, there is not Fig. S3 in the supplement of this passage.
line 243-244: “Alkenes, aromatics and OVOCs were the three contributing chemical groups to O3 formation”, should be “the three biggest contributors”.
- AC2: 'Reply on RC2', Lulu Cui, 28 Mar 2022
Lulu Cui et al.
Lulu Cui et al.
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