the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Diagnosing ozone-NOx-VOC sensitivity and revealing causes of ozone increases in China based on 2013–2021 satellite retrievals
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
Abstract. Particulate matter (PM2.5) concentrations in China have decreased significantly in recent years, but surface ozone (O3) concentrations showed upward trends at more than 71 % of air quality monitoring stations from 2015 to 2021. To reveal causes of O3 increases, O3 production sensitivity is accurately diagnosed by deriving regional threshold values of satellite tropospheric formaldehyde-to-NO2 ratio (HCHO / NO2), and O3 responses to precursors changes are evaluated by tracking volatile organic compounds (VOCs) and NOx with satellite HCHO and NO2. Results showed that the HCHO / NO2 ranges of transition from VOC-limited to NOx-limited regimes vary apparently among Chinese regions. VOC-limited regimes are widespread found over megacity clusters (North China Plain, Yangtze River Delta, and Pearl River Delta) and concentrated in developed cities (such as Chengdu, Chongqing, Xi’an, and Wuhan). NOx-limited regimes dominate most of the remaining areas. From 2013 to 2021, satellite NO2 and HCHO columns showed an annual decrease of 3.7 % and an increase of 0.1 %, respectively, indicating an effective reduction in NOx emissions but a failure reduction of VOC emissions. This finding further shows that O3 increases in major cities occur because the Clean Air Action Plan only reduces NOx emissions without effective VOC control. Two cases in Beijing and Chengdu also verified that NOx reduction alone or VOC increase leads to O3 increases. Based on the O3–NOx–VOC relationship by satellite NO2 and HCHO in Beijing, Chengdu, and Guangzhou, the ozone concentration can be substantially reduced if the reduction ratio of VOCs / NOx is between 2 : 1 and 4 : 1.
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Jie Ren and Shaodong Xie
Status: final response (author comments only)
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RC1: 'Comment on acp-2022-347', Anonymous Referee #1, 03 Jul 2022
This study combined satellite observations of NO2 and HCHO with surface air quality measurements over China to characterize ozone formation sensitivities and its long-term changes. A methodology largely consistent with Jin et al. (10.1021/acs.est.9b07785, 2020) were applied to harmonize long-term data from OMI and TROPOMI, and to diagnose the ozone sensitivity regimes. Then changes of satellite NO2 and HCHO were used to interpret the recent ozone increases, which is mainly attributed to NO2 reductions while VOC changed little in the context of the VOC-limited regime. Two examples showing ozone responses during COVID-19 lockdown were discussed to complementally support their arguments.
While the topic is definitely within the scope of ACP and the methodology & results are clearly written, easy to follow and overall sound, I have moderate reservations regarding publishing the manuscript at its present form. The main issue is about its novelty which I will outline later. I will support the publication of this paper, if the following concerns can be adequately addressed.
Major points:
- Novelty. The whole idea of using satellite observations of HCHO and NO2 to identify an indicator of ozone formation regime and to interpret ozone changes, as the authors also described, has been proposed and applied for ~two decades. In particular, I can easily list two recent ACP papers that essentially used the same idea, almost the same data and processing, applied to the same domain (China) and overall consistent time period (since 2010s), and came up with consistent conclusions: Wang et al. (10.5194/acp-21-7253-2021, 2021) and Li et al. (10.5194/acp-21-15631-2021, 2021). I merely found substantially novel/additional insights from this manuscript relative to these two papers. In the next round the review, the authors should highlight the unique points in their manuscript relative to these two papers to justify that their paper is substantially novel.
- Potentially unnecessary data processing. The idea of "harmonization" of OMI and TROPOMI data might be borrowed from Jin et al. (10.1021/acs.est.9b07785, 2020), but it is odd to be used here for 2013-2021, which is already fully covered by OMI. The "harmonization" process will introduce potentially more uncertainties, especially considering the short time period (thus the climatological differences between the two sensors and the adjustments based on that will be more contaminated by meteorological anomalies). Furthermore, I do not see any unique insights/interpretations that are only available at <20 km spatial scale in the manuscript. If the "harmonized data" is still used in the revision, the authors should evaluate how different the results become if only using OMI data, and justify that these differences are strong and due to the unique information from TROPOMI.
- The COVID-19 analysis. Section 3.4 is confusing to me. First, the main topic is to discuss long-term changes (and maybe relevance with emission regulations), I believe this short-term ozone responses to NO2 and HCHO do not support the long-term analysis before. Second, the Chinese lockdown is during February and March, 2020. The authors selected April for Beijing, and May for Chengdu, why? Indeed, both NO2 and HCHO do not show the "COVID-typical" reductions to me. Third, can the current analysis for one month in three years, each year with their unique meteorological conditions/variations, really support the attribution of these ozone responses to be driven by emissions? Including more years that potentially envelope possible meteorological variabilities seem more reasonable to me.
- Strong arguments about potential PM effects. The authors concluded that "Our study highlights that the root cause of ozone increase in major regions is the significant reduction of NOx alone without effective control of VOC and not the concurrent decreases in the PM2.5 level as suggested in previous studies". However, their results cannot support this argument. PM2.5 and NOx decrease simultaneously during the investigated period, therefore ozone increases are also associated with PM2.5 reductions. Whether the chemical regime is NOx-limited or NOx-saturated does not rule out the PM effects, since uptake of HO2 will affect both regimes according to Li et al. (2019). If the authors would like to retain their strong arguments that PM is not affecting the ozone production, they will need to validate that ozone at similar HCHO and NO2 level (e.g. bins in Figure 3a, with meteorological effects also minimized/normalized) stays the same over time.
Minor points:
1) The "x" in "NOx" should be a subscript.
2) Line 63-64: "highly controversial" due to one paper finding inconsistency over one site?
3) Beijing and Chengdu are selected to look at COVID-19 effects (Figure 7), and Beijing, Chengdu and Guangzhou are used to investigate optimal emission regulation (Figure 8). Why are these cities selected? Can they represent other cities?
4) Line 81: The "reference state" was at 273 K before September 2018, and at 298 K afterwards. Is this factor considered? Should be included in the introduction.
5) Line 97-103: please provide more detailed introduction of the data. How the re-gridding is done? What is the temporal resolution of data used?
6) Line 118: Please provide a map of the 9 regions for people unfamiliar with geography of China.
7) Figure 3a: Some isopleth lines will greatly help guide the audience.
8) Figures 2/4/5/6: Are the annual maps really necessary? Maybe one map for each phase (2013, 2019, 2021) will be enough?
9) Figure 7: Without e.g. a modeling framework to isolate each contribution, just listing all the monthly-average numbers of these parameters cannot support the discussion in Section 3.4
10) Figure 8 and its relevant discussion: It is unusual to introduce more results in the last section. Please consider re-organize.
References:
Li, K., Jacob, D. J., Liao, H., Zhu, J., Shah, V., Shen, L., Bates, K. H., Zhang, Q., and Zhai, S.: A Two-Pollutant Strategy for Improving Ozone and Particulate Air Quality in China, Nat. Geosci., 12, 906–910, https://doi.org/10.1038/s41561-019-0464-x, 2019.
Li, R., Xu, M., Li, M., Chen, Z., Zhao, N., Gao, B., and Yao, Q.: Identifying the spatiotemporal variations in ozone formation regimes across China from 2005 to 2019 based on polynomial simulation and causality analysis, Atmos. Chem. Phys., 21, 15631–15646, https://doi.org/10.5194/acp-21-15631-2021, 2021.
Wang, W., van der A, R., Ding, J., van Weele, M., and Cheng, T.: Spatial and temporal changes of the ozone sensitivity in China based on satellite and ground-based observations, Atmos. Chem. Phys., 21, 7253–7269, https://doi.org/10.5194/acp-21-7253-2021, 2021.
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AC1: 'Reply on RC1', Shaodong Xie, 25 Jul 2022
We are grateful to the reviewer for the thoughtful and constructive comments, which are helpful for significantly improving the manuscript. We will respond to each comment in detail in the revised manuscript. The short responses are provided here first.
1. Novelty. Firstly, higher resolution TROPOMI data is used to improve the accuracy of estimating the HCHO/NO2 thresholds in different regions of China. Secondly, some methodology details for establishing the relationship between O3 and HCHO/NO2 are different from those mentioned by the reviewer. Thirdly, O3 sensitivity distributions in China are updated to 2021 using these thresholds and the reasons why ozone concentrations increased in recent years combined with long-term variation trends of ozone precursors and short-term change cases are explored. Furthermore, optimal VOC/NOx reduction ratios for three typical cities are provided. We will emphasize uniqueness and novelty in the revised manuscript.
2. Significance of TROPOMI data.The higher resolution of TROPOMI satellite data enables a more accurate match between the location of ground-based O3 monitoring stations and the grid of satellite data, thus allowing a more accurate derivation of HCHO/NO2 thresholds and a more accurate reflection of the spatial distribution of ozone sensitivity. In addition, OMI data at some times are missing in the products from QA4ECV. Therefore, we adjusted the OMI data before 2018 to combine it with the TROPOMI satellite data. The relevant explanation will be added in the revised manuscript.
3. Cases during COVID-19. This section is to verify the O3 sensitivity in cities in typical cases with the particular changes in emission and ozone concentration in the short term.
This study focuses on the O3 sensitivity from April to September, the period when ozone exceedances are most likely to occur. In April 2020, Beijing is still under strict restrictions because of the epidemic control. Therefore, NO2 concentration is significantly lower than those in 2019 and 2021, which is caused by the still restricted anthropogenic activities rather than by the air pollution control actions. Le et al. also reported a similar conclusion that NO2 decreased and O3 increased during the COVID-19 outbreak. The significant increase in HCHO concentrations in Chengdu in May 2020 implies an increase in VOC emissions. Song et al., 2021 also reported an increase in VOC concentrations. It could be explained by the vigorous development of stall business in Chengdu at that time in order to resumption of work and production. In both cases, the decrease in NOx and the increase in VOC, as well as unfavorable meteorological conditions, contributed to the ozone pollution events.
4. PM effects. Some studies suggested that concurrent decreases in the PM2.5 level may be a potential driver of ozone increases in China, which may increase solar radiation and weaken the aerosol sink of HO2 radicals and thus stimulate ozone production. However, the summertime MDA8 O3 enhancement due to changes in emissions and PM2.5 levels in NCP during 2013-2017 estimated by Li et al. (1 ppb year-1) is insufficient to explain the observed trend (3.3 ppb year-1) (Lu et al.), which indicates that the effect of PM2.5 is not the essential cause of the deterioration of ozone pollution.
The results in this study show that it is the variation of the ozone precursors VOC and NOx that is responsible for the ozone concentrations. Our previous study also shows that O3 concentrations in Beijing have declined in recent years in parallel with the significant decline in PM2.5 concentrations, suggesting that the appropriate emission reduction ratio of VOC to NOx can control both PM2.5 and O3 pollution. A simple emphasis on “decreasing PM2.5 leads to increasing ozone concentrations” could mislead the government to make the wrong policy decisions. More discussions will be supplied in the revised manuscript.
References:
Le, T., Wang, Y., Liu, L., Yang, J., Yung, Y. L., Li, G., and Seinfeld, J. H.: Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China, Science, 369, 702, https://doi.org/10.1126/science.abb7431, 2020.
Li, K., Jacob, D. J., Liao, H., Shen, L., Zhang, Q., and Bates, K. H.: Anthropogenic drivers of 2013-2017 trends in summer surface ozone in China, P. Natl. Acad. Sci. Usa., 116, 422-427, https://doi.org/10.1073/pnas.1812168116, 2019.
Lu, X., Zhang, L., Wang, X., Gao, M., Li, K., Zhang, Y., Yue, X., and Zhang, Y.: Rapid Increases in Warm-Season Surface Ozone and Resulting Health Impact in China Since 2013, Environmental Science & Technology Letters, 7, 240-247, https://doi.org/10.1021/acs.estlett.0c00171, 2020.
Song, M., Feng, M., Lin, X., Tan, Q., Song, D., Liu, H., Dong, H., Zeng, L., Lu, K., and Zhang, Y.: Causes and sources of heavy ozone pollution in Chengdu (in Chinese), China Environmental Science, 1-11, https://doi.org/10.19674/j.cnki.issn1000-6923.20210923.004, 2021
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RC2: 'Comment on acp-2022-347', Anonymous Referee #2, 15 Aug 2022
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AC2: 'Reply on RC2', Shaodong Xie, 21 Aug 2022
We thank the reviewer for the thoughtful and constructive comments, which will greatly assist in revising the manuscript. Here is a short response to the major comments first.
1.Indeed, ozone is produced from NO2, and continued reduction of NOx will eventually reduce O3 concentrations. Our results show that the NOx-limited regime exists in a large area of China currently, where NOx reduction is effective in controlling ozone pollution. However, at present, key city clusters and urban areas are dominated by VOC-limited and transitional regimes. If the scheme of no VOC reduction and NOx reduction only is adopted, the O3 concentration cannot be effectively reduced until NOx is reduced to a very low level to lead the O3 formation regime to shift to NOx-limited, which requires a very long time and high cost. In contrast, a strong effort to reduce VOCs and increase the VOCs/NOx reduction ratio is the immediate and effective way to reduce O3 concentrations.
The results of Wang et al. (2022) show that VOC reduction would significantly decrease O3, while NOx reduction would only slightly decrease O3 at two urban sites in Beijing and Shanghai from June to August after 2019. This is consistent with our findings from April to September in Beijing and Shanghai that VOC reduction is more effective than NOx reduction for controlling O3 pollution. We provide the spatial distribution of ozone sensitivity in China, and different regions should adopt different emission reduction strategies.
2.Although the HCHO yields of different VOC species differ, the changes in satellite HCHO can roughly indicate changes in total VOC emissions, which has been applied in several previous studies. (Li et al., 2020; Shen et al., 2019; Zhu et al., 2014)
Our results show that there is no significant overall decrease in satellite HCHO concentrations in most of eastern China since 2013, which is similar to the estimated trends of anthropogenic VOC and biogenic VOC emissions in China (Zheng et al., 2018; Simayi et al., 2022; Li et al., 2020). Biogenic VOC emissions are difficult to control, and anthropogenic VOC emissions are much higher than biogenic VOC emissions in urban areas of China, so it is the lack of anthropogenic VOC emission reduction that has not significantly decreased HCHO.
Overall, the long-term changes in HCHO are driven by several factors, such as anthropogenic and biogenic emissions, OH abundance, and NOx concentrations, which deserve further investigation in future studies using more adequate observational data. Most relevant to our study is that HCHO has not declined as dramatically as NO2, i.e., the overall change in VOC is much smaller than NOx reductions over the past 9 years.
References:
Li, K., Jacob, D. J., Shen, L., Lu, X., De Smedt, I., and Liao, H.: Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences, Atmos. Chem. Phys., 20, 11423-11433, https://doi.org/10.5194/acp-20-11423-2020, 2020.
Li, L., Yang, W., Xie, S., and Wu, Y.: Estimations and uncertainty of biogenic volatile organic compound emission inventory in China for 2008?2018, Sci Total Environ, 733, 10.1016/j.scitotenv.2020.139301, 2020.
Shen, L., Jacob, D. J., Zhu, L., Zhang, Q., Zheng, B., Sulprizio, M. P., Li, K., De Smedt, I., Abad, G. G., Cao, H., Fu, T., and Liao, H.: The 2005-2016 Trends of Formaldehyde Columns Over China Observed by Satellites: Increasing Anthropogenic Emissions of Volatile Organic Compounds and Decreasing Agricultural Fire Emissions, Geophys. Res. Lett., 46, 4468-4475, https://doi.org/10.1029/2019GL082172, 2019.
Simayi, M., Shi, Y., Xi, Z., Ren, J., Hini, G., and Xie, S.: Emission trends of industrial VOCs in China since the clean air action and future reduction perspectives, Sci. Total Environ., 826, 153994, https://doi.org/10.1016/j.scitotenv.2022.153994, 2022.
Wang, W. J., Parrish, D. D., Wang, S. W., Bao, F. X., Ni, R. J., Li, X., Yang, S. D., Wang, H. L., Cheng, Y. F., and Su, H.: Long-term trend of ozone pollution in China during 2014-2020: distinct seasonal and spatial characteristics and ozone sensitivity, Atmos. Chem. Phys., 22, 8935-8949, https://doi.org/10.5194/acp-22-8935-2022, 2022.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095-14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zhu, L., Jacob, D. J., Mickley, L. J., Marais, E. A., Cohan, D. S., Yoshida, Y., Duncan, B. N., Abad, G. G., and Chance, K. V.: Anthropogenic emissions of highly reactive volatile organic compounds in eastern Texas inferred from oversampling of satellite (OMI) measurements of HCHO columns, Environ. Res. Lett., 9, https://doi.org/10.1088/1748-9326/9/11/114004, 2014.
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AC2: 'Reply on RC2', Shaodong Xie, 21 Aug 2022
Jie Ren and Shaodong Xie
Jie Ren and Shaodong Xie
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