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. 2024 Feb 22;58(9):4291–4301. doi: 10.1021/acs.est.4c00637

Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies

Qihou Hu †, Xiangguang Ji ‡,*, Qianqian Hong §, Jinhui Li ∥, Qihua Li ∥, Jinping Ou ⊥, Haoran Liu ∥, Chengzhi Xing †, Wei Tan †, Jian Chen #, Bowen Chang ∥, Cheng Liu ∇,†,○,◆,*
PMCID: PMC10919071  PMID: 38385161

Abstract

graphic file with name es4c00637_0005.jpg

Photochemical ozone (O3) formation in the atmospheric boundary layer occurs at both the surface and elevated altitudes. Therefore, the O3 formation sensitivity is needed to be evaluated at different altitudes before formulating an effective O3 pollution prevention and control strategy. Herein, we explore the vertical evolution of O3 formation sensitivity via synchronous observations of the vertical profiles of O3 and proxies for its precursors, formaldehyde (HCHO) and nitrogen dioxide (NO2), using multi-axis differential optical absorption spectroscopy (MAX–DOAS) in urban areas of the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions in China. The sensitivity thresholds indicated by the HCHO/NO2 ratio (FNR) varied with altitude. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude, particularly on heavily polluted days. The NOx-limited and transition regimes played more important roles throughout the entire boundary layer than at the surface. The feasibility of extreme NOx reduction to mitigate the extent of the O3 pollution was evaluated using the FNR–O3 curve. Based on the surface sensitivity, the critical NOx reduction percentage for the transition from a VOC-limited to a NOx-limited regime is 45–72%, which will decrease to 27–61% when vertical evolution is considered. With the combined effects of clean air action and carbon neutrality, O3 pollution in the YRD and PRD regions will transition to the NOx-limited regime before 2030 and be mitigated with further NOx reduction.

Keywords: O3 formation sensitivity, vertical profile, ground-based remote sensing, formaldehyde to NO2 ratio (FNR), extreme NOx reduction

Short abstract

This paper explores O3 formation sensitivity at different altitudes based on vertical observations and evaluates the feasibility of extreme NOx reduction to mitigate O3 pollution with considering the vertical evolution of O3 pollution.

1. Introduction

Since the discovery of ambient ozone (O3) in photochemical smog in Los Angeles, United States in the 1940s and 1950s,1 ground-level O3 pollution has become a major environmental concern globally. Governments worldwide have imposed pollution prevention and control measures to mitigate the extent of O3 pollution. Since the Clean Air Act was implemented in 1970 in the United States, surface O3 levels have shown a slow downward trend from the 1980s, although with large interannual variability.2,3 Nevertheless, as high as 90% of the noncompliance to air quality in the United States was caused by O3 pollution in 2016.4 Furthermore, the results of O3 pollution reduction measures in Europe and Japan have not been evident, and the O3 levels in Japan have even shown a slight upward trend.5 In China, the Action Plan for Air Pollution Prevention and Control issued in 2013 resulted in considerable reduction in ambient PM2.5 and gaseous pollutants such as sulfur dioxide (SO2) and nitrogen dioxide (NO2); however, O3 pollution has presented an increasing trend.6,7

One reason for the difficulty in mitigating O3 pollution is that lower tropospheric O3 is mainly generated through photochemical reactions of its precursors, nitrogen oxide (NOx = NO2 + NO) and volatile organic compounds (VOCs), instead of through direct emissions.8 Therefore, O3 pollution is controlled by NOx or VOC levels, depending on which precursor is the limiting reagent in the atmosphere. Accordingly, there are three O3 formation sensitivity regimes: the NOx-limited, VOC-limited, and transition regimes.9 Understanding the sensitivity of the O3 formation is crucial to developing pollution control strategies.

Another important reason for the difficulty in mitigating O3 pollution is that photochemical O3 formation occurs not only at the ground level but also at elevated altitudes. According to vertical observations using ozonesondes, tethered balloon detection systems, and ozone lidars, O3 concentrations in the upper boundary layer usually exceed that at the surface.10−12 Vertical exchange of O3 from elevated altitudes can contribute to >20% of the variations in surface O3.13,14 For better O3 pollution prevention and control, O3 production must be reduced not only near the ground but also in the middle and upper boundary layers. Therefore, it is necessary to identify the sensitivity of the O3 formation at different heights.

The O3 formation sensitivity is precisely identified based on the VOCs to NOx ratio (VOCs/NOx) using the empirical kinetic modeling approach (EKMA) curve of O3–VOCs–NOx.15 Because of the broad range of VOC species, a complete evaluation of the O3 formation sensitivity requires synchronous measurements of hundreds of gaseous species. HCHO is mainly generated by the oxidization of most VOCs and can be used as a proxy for total VOCs.16 Furthermore, because the majority of NOx in ambient air exists as NO2, NO2 can be applied as a proxy for NOx.17 To rapidly identify key precursors, the tropospheric formaldehyde (HCHO) to NO2 ratio (FNR), calculated using vertical column densities (VCDs) of tropospheric HCHO and NO2 from satellite remote sensing, is widely used to replace ground-level VOCs/NOx and determine the sensitivity at the surface in the United States,18 China,19 and Europe.20 However, tropospheric column FNR may not be coincident with surface FNR, due to the inhomogeneity of the vertical distributions of HCHO and NO2. The applicability of tropospheric column FNR to determine the O3 formation sensitivity at the ground level should be evaluated according to the vertical observations.

Up to now, there have been few observational studies concerning FNR and O3 formation sensitivity at different altitudes, because it is difficult to obtain the vertical profiles of O3 and its precursors simultaneously. MAX–DOAS has been widely used to obtain the profiles of the precursors, HCHO and NO2;21−23 whereas, because MAX–DOAS quantifies trace gas profiles using collected scattered sunlight at multiple elevation angles, high stratospheric O3 levels make the detection of lower tropospheric O3 very difficult. Lin et al.24 and Hong et al.25 used FNR profiles from MAX–DOAS to explore the vertical distribution of O3 formation sensitivity. Owing to the lack of O3 profiles, the VOC-limited, transition, and NOx-limited regime thresholds in elevated layers were presumed to be the same as those at the surface. Xing et al.26 and Ren et al.27 studied the O3 formation sensitivity in elevated layers using the O3 profiles from lidar and the precursor profiles from MAX–DOAS; however, the campaigns lasted for less than one month and the conclusions tended to be qualitative.

Recently, we developed a method for retrieving lower tropospheric O3 profiles from MAX–DOAS that uses the total O3 profile from satellite remote sensing to account for the influence of stratospheric O3.28 Herein, we used the profiles of O3, HCHO, and NO2 in the lower troposphere (0–3000 m) simultaneously obtained using MAX–DOAS to explore the O3 formation sensitivities at different altitudes in urban areas of three key regions of China: the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions, which are the three major Chinese urban agglomerations and are confronted with serious O3 pollution.29−31 Synchronous observations of O3 and proxies for its precursors using the same instrument can greatly reduce the system bias between different data sets. Precursor reduction strategies for O3 pollution prevention, particularly the feasibility of an extreme NOx reduction strategy, will be discussed according to the vertical evolution of O3 formation sensitivity. This study will contribute to a better understanding of the causes of O3 pollution and preventative approaches from the perspective of vertical evolution.

2. Methods

2.1. MAX–DOAS Observation and Retrieval

Ground-based MAX–DOAS measurements were continuously conducted from January 1 to December 31, 2022 at three sites in China from our Ground-Based Hyperspectral Stereoscopic Remote Sensing Network.21 The sites were the Chinese Academy of Meteorological Sciences (CAMS, 116.32° E, 39.93° N) in urban Beijing in the BTH region, the Anhui University (AHU, 31.78° N, 117.18° E) in urban Hefei in the YRD region, and the Guangzhou Institute of Geochemistry, Chinese Academy of Sciences (GIG, 23.15° N, 113.36° E) in urban Guangzhou in the PRD region (Figure S4).

The MAX–DOAS instrument consists of a telescope, two spectrometers covering the wavelength ranges of 296–408 nm and 420–565 nm, respectively, and a controlling computer. The vertical profiles of trace gases were retrieved from scattered sunlight observed at different elevation angles. A full MAX–DOAS scan consisted of 11 elevation viewing angles (1°, 2°, 3°, 4°, 5°, 6°, 8°, 10°, 15°, 30°, and 90°) and lasted for about 12 min.

The vertical profiles of O3, HCHO, and NO2 in the lower troposphere were retrieved using a profile algorithm developed in our previous studies.23,26,32 Briefly, the sunlight collected by MAX–DOAS at different elevation angles was first analyzed using the DOAS method based on the Lambert–Beer law, which extracts the integrated trace gas concentrations based on their characteristic absorption structures in their specific wavelength range. In this study, the QDOAS software package developed by the Royal Belgian Institute for Space Aeronomy was used to analyze the collected spectrum (BIRA–IASB, Brussels, Belgium, http://uv-vis.aeronomie.be/software/QDOAS/, accessed on September 10, 2023). Fitting intervals of 320.0–340.0, 322.5–358, and 338.0–370.0 nm were used to retrieve the differential slant column densities (dSCDs) of O3, HCHO, and NO2, respectively. The variation of dSCDs with elevation angles contains information about the vertical distribution of trace gases. As such, vertical profiles of trace gases were retrieved from the dSCDs at different elevation angles using an optimal estimation-based profile retrieval algorithm with considering aerosol optical characteristics.33 In addition, daily stratospheric O3 profiles from TROPOspheric Monitoring Instrument (TROPOMI) satellite measurements34 were included in the radiative transfer model (RTM) simulation for tropospheric O3 profile retrieval to account for the influence of stratospheric O3 absorption on the retrieval. Detailed information on the O3 profile retrieval algorithms and their validations can be found in our previous study.28

2.2. Ancillary Data

Numerous previous studies adopted tropospheric column FNR from satellite remote sensing to replace ground-level FNR and determine the O3 formation sensitivities. To evaluate the applicability of tropospheric column FNR on the determination of O3 formation sensitivities at the surface, we will compare the tropospheric column FNR and ground-level FNR. Therefore, VCDs of tropospheric HCHO and NO2 were retrieved from the TROPOMI spectrum using the algorithms developed by the University of Science and Technology of China (USTC).34−36 To explore the sensitivity of the O3 formation under different air qualities, we used the daily maximum 8 h average (MDA8) O3 levels from the China National Environmental Monitoring Center (CNEMC) network. The observation days were divided into clean days (MDA8 < 100 μg m–3), lightly polluted days (100 μg m–3 ≤ MDA8 < 160 μg m–3), and heavily polluted days (MDA8 ≥ 160 μg m–3) according to the ambient air quality standard of China. The CNEMC sites closest to the CAMS, AHU, and GIG sites are 1006A, 1270A, and 1349A, respectively.

2.3. Determination of the O3 Formation Sensitivities

Based on the synchronous O3, HCHO, and NO2 profiles with the same temporal and vertical resolutions obtained using MAX–DOAS, the O3 formation sensitivities in different layers, as indicated by the FNR, were determined following the method of Jin et al.18 and Ren et al.37 First, the data in the respective vertical layer were arranged in the order of the FNR values from small to large, and then every ten sets of data were grouped into a bin. Then, the binned O3 concentrations in the respective layer are plotted as a function of binned FNRs. O3 first increased and then decreased with the increase in FNR. Therefore, polynomial rather than linearity is used to fit the FNR curve. This method has been also used by previous studies in China25,38 and the United States.39 Through testing, the third-order polynomial showed the best performance and was chosen to determine the threshold of ozone formation sensitivity. This method assumes that the peak plateau of the fitted curve indicates the transition from a VOC-limited regime to a NOx-limited regime in the respective layer. The transition regime is regarded as the FNR range spanning the top 10% of the highest O3 distribution.25

2.4. Calculation of the FNR for the Entire Boundary Layer

To include the impact of O3 formation sensitivity in different layers, the FNR for the entire boundary layer (FNRBL) was calculated using the measured FNRs in the individual layers (FNRi) according to the following equations:

2.4. 1

where Wi is the weight of each layer, which is calculated using the average profile of O3.

2.4. 2

where Ci is the average O3 concentration in layer i and Hi is the height of layer i. The thresholds for FNRBL were also determined using the average O3 profile as the weight.

2.4. 3
2.4. 4
2.4. 5

where fpeak–BL, fVOC–BL, and fNOx–BL are the FNR thresholds for the entire boundary layer and fpeak–i, fVOC–i, and fNOx–i are the FNR thresholds for layer i.

3. Results and Discussion

3.1. Vertical Evolution of O3 and Its Precursors

Besides production from the photochemical reaction of the precursors, the O3 concentrations are also affected by vertical mixing and regional transport. Accurate determination of O3 formation sensitivity needs the O3 production rate, which is calculated by the photochemical box model.40 The simulation of the box model needs dozens of air pollutant species, especially the VOC species. However, the observation of VOC species is very difficult, especially at elevated altitudes. Fortunately, numerous recent studies have proved that O3 abundance can replace O3 production rate to investigate O3 formation sensitivities at the surface.18,19,37,41,42 Therefore, in this study, the observed O3 concentrations and FNRs were employed to diagnose the O3 formation sensitivities in different vertical layers.

To minimize the influence of vertical mixing and regional transport, which is associated with meteorological conditions, we only used data from 12:00–17:00 local time, when photochemical reactions are the strongest, to explore the vertical evolution of the O3 pollution. Additionally, the data in the winter (January, February, and December) was excluded because of weak O3 formation. The trend of the O3 concentrations after these selections could approximately represent the O3 production. Moreover, the influences of precursors and meteorological factors on O3 profiles were compared (see Text S1). In general, although the effect of meteorological conditions varied in different cities, precursors always played a dominant role in the trend of the presence of O3 in the vertical layers. In the following, the vertical evolutions of O3, proxies for the precursors, and O3 formation sensitivity is focused.

NO2 in urban Beijing, Hefei, and Guangzhou was generally concentrated in the lower boundary layer (Figures 1d–1f), particularly within the height of 500 m close to the emission sources, whereas HCHO was widely distributed in the whole boundary layer (Figures 1g–1i) due to the oxidation of methane and VOCs at higher altitudes.43 Nevertheless, the refined vertical structures of NO2 and HCHO in the three cities showed a discrepancy, causing different vertical profiles of O3. NO2 reached the peak mainly at the surface and abruptly decreased above 100 and 200 m in Beijing and Hefei, respectively. Accordingly, the concentrations of O3 first increased and then decreased with increasing altitude in urban Beijing and Hefei (Figures 1a and 1b). During the campaign, the highest concentrations of O3 in the vertical direction in the two cities occurred in the layer at an altitude of 200–300 m (200–300 m layer). Additionally, the concentrations of O3 at altitudes of 100–400 m in Beijing and 100–500 m in Hefei exceeded those in the surface layer (0–100 m). Net O3 production is usually more intensive at elevated altitudes than at the surface because of the weaker NO titration effect and stronger sunlight.44 Thus, precursors emitted at the surface are transported upward to the middle and upper boundary layers where they generate O3 before returning to the surface.13,45

Figure 1.

Figure 1

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Mean diurnal variations in the vertical distribution of (a–c) O3, (d–f) HCHO, and (g–i) NO2 in urban Beijing (upper panel), Hefei (middle panel), and Guangzhou (lower panel) from March to November, 2022. (j–l) The vertical distribution of the FNR and the thresholds of O3 formation sensitivity within 1000 m in urban Beijing, Hefei, and Guangzhou. The bottoms and tops of the boxes in subfigures j–l represent the 25th and 75th percentiles, respectively. The dots and lines within the boxes represent the mean and median, respectively. The whiskers on the left and right of the boxes indicate the 10th and 90th percentiles, respectively. The red and blue lines represent the thresholds of the VOC-limited and NOx-limited regimes, respectively.

Otherwise, the inverse vertical profiles of HCHO and NO2, with higher concentrations above 100 m compared with the surface layer, were observed in Guangzhou. Particularly, the average NO2 concentration in the 200–300 m layer was 59% higher than the ground-level mean concentration (Figure 1f). The inverse structures of NO2 were possibly induced by the emissions from high elevation sources and were observed in Guangzhou and Shenzhen located in the PRD region.46,47 The inverse NO2 structures probably caused an even more intensive NO titration effect at elevated altitudes. Thus, the maximum O3 concentrations occurred at an altitude of 0–200 m in urban Guangzhou, whereas the concentration of O3 in the 200–300 m layer greatly dropped (Figure 1c). Even if the O3 level at the surface was higher than at elevated altitudes, O3 in the middle and upper boundary layers could also affect surface concentrations at the surface, because vertical diffusion of surface air pollutants depends on concentration gradients between layers.48

From clean days to polluted days, the O3 concentrations at the three MAX–DOAS sites evidently increased in the boundary layer from the surface to ∼1000 m (Figures S5–S7). There was little variation in the concentration of the O3 above 2000 m. Besides, higher O3 concentrations in the free troposphere than in the boundary layer were only found during the clean days in Beijing. It indicated that the O3 pollution was a result of photochemical generation rather than injection from the free troposphere and stratosphere. The largest increments during polluted days in O3 in urban Beijing occurred in the 200–300 m layer (91% increase from clean days to lightly polluted days) and the 100–200 m layer (195% increase from clean days to heavily polluted days). Similarly, the largest increment in O3 in urban Hefei occurred in the 200–300 m layer during both lightly and heavily polluted days. However, the O3 concentration in urban Guangzhou increased the greatest at the surface (99% and 127% on the lightly polluted and heavily polluted days, respectively).

Likewise, the O3 precursors showed substantial variation under different air quality conditions (Figures S5–S7). HCHO concentrations greatly increased below 1600 m during polluted days at the three sites. At the CAMS site in Beijing, HCHO increased by >200% in all layers below 1200 m from the clean days to heavily polluted days, whereas NO2 levels generally decreased. The opposite trends of HCHO and NO2 on polluted days were caused by different sources. HCHO is mainly a secondary product of VOCs from photochemical reactions. NOx is mainly emitted as NO, which is rapidly transformed to NO2 by O3 in the ambient air.49 Thus, NO2 can be considered as a primary pollutant. Because the clean days and polluted days alternated during our campaign, the emissions of VOCs and NOx in different air quality conditions could not be greatly varied. Therefore, the changes in HCHO and NO2 were probably caused by meteorological conditions. Heavy pollution usually occurred on sunny days with high temperatures and intensive sunlight. Stronger photochemical reactions caused more HCHO generated and more NO2 photodegraded.

3.2. O3 Formation Sensitivity at Different Altitudes

The O3 concentrations at altitudes below 1600 m showed a strong relationship with the FNRs in urban Beijing, with Pearson correlation coefficients >0.5 (Figures 2a–2c and Table S1). The FNR value with peak O3 concentrations (fpeak) in the surface layer in Beijing was 4.7, with the thresholds of the VOC-limited regime (fVOC) and the NOx-limited regime (fNOx) equal to 4.4 and 5.0, respectively (Figure 2a). The VOC-limited regime was dominant, with a contribution of 97.2%, whereas the contributions of the NOx-limited and transition regimes were only 1.6% and 1.2%, respectively (Figure 3a).

Figure 2.

Figure 2

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Fitting of O3 concentrations as a function of the binned FNRs based on MAX–DOAS observations for the 0–100 m layer (left panel), 400–500 m layer (middle panel), and 800–900 m layer (right panel) for sites in urban (a–c) Beijing, (d–f) Hefei, and (g–i) Guangzhou. The blue solid line is the fitted third order polynomial curve and the shadings represent 95% confidence and 95% prediction bands, respectively. The red solid line represents the peak of the fitted curve and the vertical shading indicates the range over the top 10% of the fitted curve (transition regime).

Figure 3.

Figure 3

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Contribution of the VOC-limited, transition, and NOx-limited regimes in different layers below 1000 m in the afternoon from March to November 2022 in (a) urban Beijing, (b) Hefei, and (c) Guangzhou.

Because of a lack of continuous HCHO monitoring, O3 formation sensitivity at the ground level is usually determined using the tropospheric VCDs of HCHO and NO2 from satellite remote sensing and O3 concentrations from in situ observations.18,37,50 Schroeder et al.40 and Ren et al.37 suggested that the inhomogeneity of the vertical distributions of HCHO and NO2 may have a negative influence on determining the threshold via satellite observation. Herein, we investigated the consistency among the tropospheric column FNR from satellite remote sensing and the boundary layer and surface FNRs from MAX–DOAS observation. To ensure temporal consistency among the three data sets, we only selected surface and boundary layer FNRs during satellite overpass time. As presented in Figure S8, the boundary layer FNRs showed a highly positive correlation with surface FNRs in the three cities, with the Pearson correlation coefficient (R) above 0.92. Besides, the correlation coefficients between the tropospheric column FNRs and the surface FNRs in the three cities ranged from 0.52 to 0.75, indicating that the tropospheric column FNRs from satellite observations could roughly represent the surface FNRs to investigate O3 pollution at the surface. Moreover, we also calculated the threshold at the surface using satellite data for comparison and determined the transition regime with tropospheric FNR values between 3.1 and 3.6 (Figure S9). It indicated that the thresholds determined using different observations, such as the FNR calculated using tropospheric VCDs and surface concentrations, could not be compared. However, the distribution of the sensitivity regimes was still comparable. For instance, based on satellite observation, the contribution of the VOC-limited regime in urban Beijing was 90.0%, whereas the transition and NOx-limited regimes contributed 4.8% and 5.2%, respectively.

The sensitivity thresholds, fpeak, fVOC, and fNOx, varied in the vertical direction in urban Beijing, with higher values in most elevated layers below 1600 m than at the surface (Figure 1j and Table S1). For instance, the transition regimes indicated by the FNR occurred between 4.4 and 5.2 in the 400–500 m layer and between 4.5 and 5.4 in the 800–900 m layer (Figures 2b and 2c). Thus, if the same thresholds determined at the surface (4.4 and 5.0) were used in elevated layers, the occurrence of NOx-limited regimes would be overestimated by 20% in most layers. According to the separate thresholds in different layers, the VOC-limited regime was dominant from the surface to 2000 m, although the influence of NOx increased with an increasing elevation (Table S1). The VOC-limited, transition, and NOx-limited regimes contributed 89.6%, 5.6%, and 4.8%, respectively, in the 400–500 m layer, and 76.9%, 6.2%, and 6.9%, respectively, in the 800–900 m layer (Figure 3a). The NOx-limited regime played a decisive role at altitudes just above 2200 m (Table S1). However, the levels of the O3 in the layers above the boundary layer fluctuated within a narrow range (∼10–20 ppbv), indicating weaker photochemical O3 production.

Despite the substantial reduction in NOx emissions and minimal change in VOC emission over the past decade,51,52 the O3 formation sensitivity in urban Beijing has still not transitioned from a VOC-limited regime to a NOx-limited regime. During the heavily polluted days, the VOC-limited regime still dominated below 1000 m, with contributions ranging from 41.0% to 100% in the different layers (Table S4). For further analysis, we examined a typical heavily polluted episode in Beijing (June 25) with an O3 MDA8 at the nearest CNEMC site (1006A) reaching 310 μg m–3. The O3 concentrations below an altitude of 700 m in the afternoon were all >100 ppbv (Figure 4a). Although the FNR in the boundary layer rose to 1.4–4.3 times the average value, the VOC-limited regime still dominated below 600 m, with no significant changes compared to the days before and after the pollution episode. The NOx-limited regime dominated only above 600 m, which increased from 14.2–20.2% during the whole campaign to 50–100% during this pollution episode (Figure 4c). It indicated that reducing VOC emissions remains the most effective measure for current O3 pollution prevention in Beijing.

Figure 4.

Figure 4

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Diurnal variations in the vertical distribution of O3 concentration (upper panel) and O3 formation sensitivity (lower panel) before, during, and after the typical heavily polluted episodes in (a and c) urban Beijing and (b and d) Guangzhou, respectively.

The O3 formation sensitivity thresholds were lower in urban Hefei and Guangzhou than in Beijing (Figures 1k and 1l). The transition regimes occurred at FNR ranges of 2.1–2.6 at the surface, 2.8–3.4 in the 400–500 m layer, and 4.2–5.3 in the 800–900 m layer in Hefei, and 2.1–2.4, 2.3–3.0, and 1.7–3.5 in the same layers, respectively, in Guangzhou (Figures 2d–2i and Tables S2 and S3). In Hefei and Guangzhou, the VOC-limited regime showed dominant sensitivity at the surface; however, the contribution of the NOx-limited regime at the surface in Hefei was much higher (18%) than in the other two cities (Figure 3b). The O3 formation sensitivity distribution showed little variation in the boundary layer in Hefei, with the contribution of the NOx-limited regime between 16% and 25%. Substantial changes in the sensitivity in Hefei occurred above 1600 m with a large increase in the proportion of the NOx-limited regime (Table S2). In urban Guangzhou, the distribution of sensitivities obviously changed from the height of 400 m (Figure 3c). In the 400–500 m layer, the contributions of the VOC-limited and NOx-limited regimes were comparable. Above 800 m in Guangzhou, the proportion of the NOx-limited regime was greater than the proportion of the VOC-limited regime. In particular, the levels of O3 between elevations of 900 and 2000 m in Guangzhou monotonously decreased with the FNRs, and thus no VOC-limited regimes were identified (Table S3).

During the heavily polluted days, the highest concentrations of O3 mainly occurred at an altitude of 300–600 m in Hefei and the surface in Guangzhou (Figures S6 and S7). The contribution of the transition and NOx-limited regimes during the heavily polluted days substantially increased in the two cities (Tables S5 and S6). During the typical pollution episodes in Guangzhou (July 23) and Hefei (June 6 to June 11), the proportions of the transitional regime evidently increased compared to the days before and after them. In Guangzhou, the contribution of the transitional regime at an altitude of 300–900 m increased from typical 13–28% for the average during the whole campaign to 17–67% during the pollution episode, while the contribution of the NOx-limited regime at an altitude of 100–300 m increased from 3.9–19% to 17–33% (Figure 4d). In Hefei, the contribution of the transitional regime at the surface increased from 9.0% during the whole campaign to 33% during the pollution episode. Besides, the contribution of NOx-limited and transitional regimes at the altitudes of 400–1000 m in Hefei increased from 20–25% and 7.3–12% to 39–44% and 11–22%, respectively (Figure S10). In general, the NOx-limited and transitional regimes were more prominent during heavily polluted days in the urban areas of the YRD and PRD regions.

A previous study pointed out that O3 formation sensitivities at the surface were affected by the boundary layer height.11 In this study, with the increase in boundary layer height, the contribution of VOC-limited and NOx-limited regimes decreased and increased, respectively, both at the surface and in the elevated layers in the three cities (Figures S11–S13). Intense solar radiation and high temperature caused both a high boundary layer height and more VOCs and NOx participating in the photochemical reactions, which generated HCHO and depleted NOx. Thus, higher boundary layer height was often accompanied by higher FNRs and more contributions of the NOx-limited regime. Besides, the contributions of the transitional regime in the vertical layers with the middle and the highest one-third boundary layer height were much higher than those with the lowest one-third boundary layer height (Figures S11–S13).

3.3. Emissions Reduction Strategy from the Perspective of Vertical Evolution

Owing to strong convection in the troposphere, especially in the boundary layer, O3 formation at elevated altitudes can also affect the O3 concentration at the surface.53 Therefore, to develop an emissions reduction strategy for precursors, VOCs, and NOx, the sensitivity of the O3 formation in different layers should be considered. Here we used the FNRBL values calculated as described in Section 2.4 to further identify the O3 formation sensitivities for the entire boundary layer.

The FNRs of the transitional zones of the O3 formation sensitivity for the entire boundary layer were 4.6–5.4, 2.9–3.6, and 2.7–3.4 in urban Beijing, Hefei, and Guangzhou, respectively (Table 1). The O3 formation sensitivity thresholds for the entire boundary layer were higher than those for the surface layer. The transition and NOx-limited regimes for the entire boundary layer contributed 13%, 31%, and 35% in urban Beijing, Hefei, and Guangzhou, respectively, which were higher than those at the surface because the sensitivities tended to be more NOx-limited in the middle and boundary layers.

Table 1. The FNR Value with O3 Concentration Peak (fpeak–BL), the Thresholds of the VOC-Limited Regime (fVOC–BL) and NOx-Limited Regime (fNOx–BL), the 25th (FNR0.25), 50th (FNR0.5), and 75th (FNR0.75) Percentiles of the FNR, and the Contribution of the VOC-Limited, Transition, and NOx-Limited Regimes for the Entire Boundary Layer in Urban Beijing, Hefei and Guangzhou.

  Beijing Hefei Guangzhou
fpeak–BL 5.0 3.3 3.1
fVOC–BL 4.6 2.9 2.7
fNOx–BL 5.4 3.6 3.4
FNR0.25 1.9 1.9 2.2
FNR0.5 0.7 1.0 1.4
FNR0.75 3.5 3.3 3.1
VOC-limited regime (%) 87.4 69.2 64.8
transition regime (%) 6.2 10.2 17.7
NOx-limited regime (%) 6.3 20.6 17.5
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Generally, VOC emissions reduction was more effective in urban areas of the megacities of the BTH, YRD, and PRD regions. The optimal reduction ratio of VOCs/NOx should be on the ridge line of the classic EKMA curve of O3–VOCs–NOx.15,54 Ren et al.37 suggested that the peak of the fitted O3–FNR curve can replace the ridge line of the EKMA curve to determine the optimal reduction ratio. In this study, the optimal reduction ratios to reduce the concentration of O3 throughout the entire boundary layer in urban Beijing, Hefei, and Guangzhou were 5.0:1, 3.3:1, and 3.1:1, respectively. These reduction ratios were slightly higher than the results (between 2:1 and 4:1) for surface O3 reported by Ren et al.37 Notably, the VOCs/NOx emissions reduction ratio of was not equal to the FNR value because the HCHO yields for different classes of VOCs and under different meteorological conditions have disparity.55,56 The relationship between the VOCs and NOx emissions and HCHO and NO2 concentrations in the atmosphere, especially the concentrations at higher altitudes, should be explored in future studies.

Although O3 pollution in the cities of China is mainly caused by VOCs, reducing anthropogenic VOC emissions is more difficult than reducing NOx emissions.57 In addition, biogenic emissions are also a major source of VOCs, which will probably further increase with global warming.58−60 However, with the proposal of the carbon-neutral target by the Chinese government, carbon dioxide (CO2) emissions will be greatly reduced in the future. Because NOx is emitted synchronously and has a strong linear relationship with CO2,61,62 further extreme NOx reduction becomes possible if the carbon-neutral target is achieved.

Using the vertical evolution of the O3 formation sensitivity from MAX–DOAS observation, the influence of extreme NOx emissions reduction on atmospheric O3 is further discussed. If we only consider the sensitivity at the surface, the critical NOx reductions without a change in VOC emissions should be 72%, 45%, and 50% in urban Beijing, Hefei, and Guangzhou, respectively, to cause the median FNR value to reach fpeak (Table 1). These reduction percentages are close to the results from the atmospheric chemical modeling by Ou et al.15 Nevertheless, considering the vertical evolution of O3 pollution, the critical NOx reductions drop to 61% and 27% in Beijing and Guangzhou, respectively (see the Graphical Abstract), because of the greater proportions of NOx-limited and transition regimes at elevated layers. However, after including the influence from higher altitudes, the change in the reduction percentage (from 45% to 42%) in Hefei is small because the proportion of the NOx-limited and transition regimes at the surface is higher than those in the other two cities, and the sensitivity distribution showed little change in the vertical direction (Figure 3b). Furthermore, the median FNRBL will exceed fNOx with reductions of 64%, 48%, and 35% in Beijing, Hefei, and Guangzhou, respectively. Then, further NOx reduction can substantially mitigate the extent of the O3 pollution. For the 75th percentile of the FNRBL value, the critical reduction proportion is 30% for Beijing, whereas those for Guangzhou and Hefei have decreased considerably to ∼0%, because the 75th percentile of the FNRBL value has reached the fpeak. Nevertheless, in order for the lowest 25th percentile of the FNR for the entire boundary layer to reach the fpeak, 55–85% of NOx emissions reduction must be achieved in the three cities.

Since the implementation of China’s clean air actions in 2010, particularly the Action Plan for Air Pollution Prevention and Control in 2013, NOx emissions have decreased considerably.63 According to the emissions inventory studies, NOx emissions in China decreased by 21% from 2013 to 2017 at an annual rate of ∼5.7%.52 According to Ozone Monitoring Instrument (OMI) satellite observations, tropospheric NO2 VCDs in the BTH and YRD regions decreased by 74% and 45%, respectively, from 2012 to 2017 (annual rates of 20% and 9%, respectively).64 Furthermore, according to the USTC’s TROPOMI product,36 the tropospheric NO2 VCDs in China further decreased from 2019 to 2022, with reductions of 24%, 27%, and 31% in the BTH, YRD, and PRD regions, respectively (Figure S14). Surface NO2 concentrations at the 1006A, 1270A, and 1349A sites of the CNEMC network in urban Beijing, Hefei, and Guangzhou decreased by 52%, 43%, and 23%, respectively, from 2015 to 2022 with annual rates of 10%, 7.6%, and 3.6%, respectively (Figure S15). If strict pollution prevention and control measures continue in the future, we conservatively predict annual decline rates for boundary layer NO2 of 5% in the BTH and YRD regions and 3% in the PRD region based on the historical data from the emissions inventory, satellite remote sensing, and in situ observations. Therefore, ambient NO2 concentrations in Hefei and Guangzhou would further decrease by 49% and 33% in 2035 (Figure S16), and the median FNRBL value in the two cities will exceed the fpeak and approach the fNOx, whereas the median FNRBL in Beijing will exceed the fpeak after 2040.

Because coal combustion for power generation and vehicle exhaust are the major sources of CO2 and NOx,65,66 NOx emissions can be greatly decreased by replacing fossil energy sources with clean energy sources in the process of achieving carbon neutrality.67 According to Zhang and Chen,68 under the scenario that carbon emissions peak in 2025, reductions in carbon emissions alone, without further clean air action, can also contribute to reducing in NOx levels by 18–26% in 2030. Overall considering the clean air action and carbon neutrality, 50% of the O3 sensitivity regimes for the entire boundary layer can exceed the fpeak and even the fNOx in urban Hefei and Guangzhou before 2030. However, even with the contribution of carbon neutrality, the median FNRBL will reach the fpeak close to 2035 in Beijing. In general, an extreme NOx reduction strategy for controlling O3 pollution in the YRD and PRD is highly feasible considering the vertical evolution of the sensitivity of the O3 formation and the carbon neutral target.

Acknowledgments

This research was supported by the National Key Research and Development Program of China (2023YFC3710500 and 2022YFC3700100), the Key Research and Development Project of Anhui Province (2023t07020015), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-DQC008), the New Cornerstone Science Foundation through the XPLORER PRIZE (2023-1033), the Youth Innovation Promotion Association of CAS (2021443), the HFIPS Director’s Fund (BJPY2022B07 and YZJJQY202303), the Hefei Comprehensive National Science Center, the Anhui Provincial Natural Science Foundation “Jianghuai Meteorological” Joint Fund (2208085UQ04), and the Natural Science Research Project of Colleges and Universities of Anhui Province (2022AH050096).

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c00637.

  • Discussions of the influences of precursors, vertical mixing and horizontal transport on O3 profiles, and description of the WRF-Chem configuration for simulating boundary layer heights and wind speeds; tables for the fitted third-order polynomial of O3 concentrations as a function of FNRs, the sensitivity regime thresholds, and the contributions of each sensitivity regime for the whole campaign and under different air quality conditions; figures for the mean O3 profiles varied with HCHO concentrations, NO2 concentrations, boundary layer heights and horizontal wind speeds, the geographical location of the MAX–DOAS sites, the mean diurnal variations in the vertical distribution of O3, HCHO, and NO2 under different air quality conditions, the time series of surface, boundary layer, and tropospheric FNRs, the fitting of surface O3 as a function of tropospheric column FNR, the diurnal variations in the vertical distribution of O3 concentration and the sensitivity regimes before, during, and after typical heavily polluted episodes in Hefei, the contribution of each sensitivity regime under different boundary layer heights, the spatiotemporal distribution of tropospheric NO2 VCDs in China, the annual NO2 concentrations at the CNEMC sites near the MAX–DOAS sites, and the predicted year-by-year reduction proportions of boundary layer NO2 in China (PDF)

Author Contributions

Qihou Hu: conceptualization, data curation, resources, investigation, software, visualization, formal analysis, writing, original draft, and review and editing. Xiangguang Ji: investigation, data curation, visualization, methodology, validation, and review and editing. Qianqian Hong: conceptualization, writing, review and editing, and formal analysis. Jinhui Li: data curation and methodology. Qihua Li: data curation, methodology, and validation. Jinping Ou: investigation and review. Haoran Liu: data curation and review. Chengzhi Xing: data curation and review. Wei Tan: data curation and review. Jian Chen: software and data curation. Bowen Chang: software and data curation. Cheng Liu: conceptualization and project administration and supervision. All authors have commented on and approved the final manuscript for publication.

The authors declare no competing financial interest.

Supplementary Material

es4c00637_si_001.pdf (2.3MB, pdf)

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