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Technical Note

Ground-Based MAX-DOAS Observations of Tropospheric Ozone and Its Precursors for Diagnosing Ozone Formation Sensitivity

by
Yuanyuan Qian
1,3,
Dan Wang
1,3,
Zhiyan Li
1,3,
Ge Yan
2,
Minjie Zhao
3,
Haijin Zhou
3,
Fuqi Si
3 and
Yuhan Luo
3,*
1
School of Microelectronics & Data Science, Anhui University of Technology, Maanshan 243032, China
2
Jianghuai Advanced Technology Center, Hefei 230088, China
3
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Sciences, Chinese Academy of Sciences, Hefei 230031, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(4), 658; https://doi.org/10.3390/rs17040658
Submission received: 12 January 2025 / Revised: 5 February 2025 / Accepted: 11 February 2025 / Published: 14 February 2025
(This article belongs to the Section Atmospheric Remote Sensing)
Browse Figures
Figure 1
<p>Multi-axis differential optical absorption spectroscopy (MAX-DOAS) instrument and the measurement site.</p> "> Figure 2
<p>Diurnal variations of NO<sub>2</sub> at the AIOFM site from MAX-DOAS measurements.</p> "> Figure 3
<p>Diurnal variations of HCHO at the AIOFM site from MAX-DOAS measurements.</p> "> Figure 4
<p>Vertical O<sub>3</sub> profiles at the AIOFM site from MAX-DOAS measurements.</p> "> Figure 5
<p>Linear fittings of surface NO<sub>2</sub> (<b>a</b>) and O<sub>3</sub> (<b>b</b>) between CNEMC in situ and MAX-DOAS measurements.</p> "> Figure 6
<p>Linear fittings of tropospheric NO<sub>2</sub> (<b>a</b>) and HCHO (<b>b</b>) VCDs between MAX-DOAS and TROPOMI measurements.</p> "> Figure 7
<p>(<b>a</b>) Third-order fitting curve between surface HCHO/NO<sub>2</sub> ratios and O<sub>3</sub>; (<b>b</b>) third-order fitting curve between surface HCHO/NO<sub>2</sub> ratios and ΔO<sub>3</sub>. The red and blue areas denote the 95% prediction interval and regime transition, respectively. The red and blue lines denote the fitting curve and the peak of the fitting curve, respectively.</p> "> Figure 8
<p>The regime transitions (blue shaded area), binned statistics of HCHO/NO<sub>2</sub> ratios (boxes), averaged values (triangles), and the calculated HCHO/NO<sub>2</sub> profile (red line).</p> "> Figure 9
<p>Average diurnal variations of O<sub>3</sub>, HCHO, NO<sub>2</sub>, and HCHO/NO<sub>2</sub> ratios on non-polluted (<b>a</b>) and polluted days (<b>b</b>).</p> "> Figure 10
<p>Diurnal variations of O<sub>3</sub> (<b>a</b>), HCHO (<b>b</b>), NO<sub>2</sub> (<b>c</b>), and HCHO/NO<sub>2</sub> ratios (<b>d</b>) in a typical O<sub>3</sub> pollution episode.</p> ">
Versions Notes

Abstract

:
Diagnosing ozone (O3) formation sensitivity using tropospheric observations of O3 and its precursors is important for formulating O3 pollution control strategies. Photochemical reactions producing O3 occur at the earth’s surface and in the elevated layers, indicating the importance of diagnosing O3 formation sensitivity at different layers. Synchronous measurements of tropospheric O3 and its precursors nitrogen dioxide (NO2) and formaldehyde (HCHO) were performed in urban Hefei to diagnose O3 formation sensitivity at different atmospheric layers using multi-axis differential optical absorption spectroscopy observations. The retrieved surface NO2 and O3 were validated with in situ measurements (correlation coefficients (R) = 0.81 and 0.80), and the retrieved NO2 and HCHO vertical column densities (VCDs) were consistent with TROPOMI results (R = 0.81 and 0.77). The regime transitions of O3 formation sensitivity at different layers were derived using HCHO/NO2 ratios and O3 profiles, with contributions of VOC-limited, VOC-NOx-limited, and NOx-limited regimes of 74.19%, 7.33%, and 18.48%, respectively. In addition, the surface O3 formation sensitivity between HCHO/NO2 ratios and O3 (or increased O3, ΔO3) had similar regime transitions of 2.21–2.46 and 2.39–2.71, respectively. Moreover, the O3 formation sensitivity of the lower planetary boundary layer on polluted and non-polluted days was analyzed. On non-polluted days, the contributions of the VOC-limited regime were predominant in the lower planetary boundary layer, whereas those of the NOx-limited regime were predominant in the elevated layers during polluted days. These results will help us understand the evolution of O3 formation sensitivity and formulate O3 mitigation strategies in the Yangtze River Delta region.

1. Introduction

In recent years, typical air pollutants involving particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2) in China have shown a descending trend following the implementation of the 12th Five-Year Plan (12th FYP) [1,2,3]. For example, tropospheric NO2 and SO2 concentrations decreased by approximately 32% and 50%, respectively, during the 12th FYP [4,5]. However, near-surface ozone (O3), which is detrimental to human health, has become a primary pollutant in many Chinese cities [6,7]. Several respiratory and lung diseases are closely related to exposure to ambient O3 [8,9]; for example, 186,000 average annual respiratory deaths were attributed to ambient O3 exposure between 2013 and 2017 [10]. In addition, ambient O3 can decrease crop yields by inhibiting photosynthesis [11,12] and contribute to climate warming through its greenhouse gas effect [13].
The O3 in the lower troposphere is a secondary pollutant formed by the photochemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOCs) under solar radiation [14]. Therefore, in many previous studies, the O3 formation sensitivity has been diagnosed using O3-NOx-VOC indicators. Sillman first diagnosed O3-NOx-VOC sensitivity using the ratios of formaldehyde (HCHO) to NOx [15]. In addition, satellite-based measurements of column HCHO-to-NO2 ratios have become an important means to diagnose O3-NOx-VOC sensitivity [16,17]. Moreover, ground-based measurements play an important role in diagnosing O3 formation sensitivity. Liu et al. [18] utilized HCHO-to-NO2 and glyoxal (CHOCHO)-to-NO2 ratios from Thermo 42i and chromatographic measurements to diagnose O3-NOx-VOC sensitivity. Qian et al. [19] diagnosed the O3 formation sensitivity at Heshan Observatory using HCHO-to-NO2 ratios via multi-axis differential optical absorption spectroscopy (MAX-DOAS) and the planetary boundary layer (PBL) O3 profiles via light detection and ranging (LIDAR) measurements. Lin et al. [20] utilized secondary HCHO-to-NO2 ratios from MAX-DOAS measurements to diagnose O3 formation sensitivity, while Ryan et al. [21] diagnosed O3 formation sensitivity in Melbourne using HCHO-to-NO2 and CHOCHO-to-NO2 ratios.
The Yangtze River Delta (YRD), accounting for 24% of China’s gross domestic product (GDP), is plagued by severe O3 pollution [22,23]. According to the data from the China National Environmental Monitoring Center (CNEMC) network, the 90th percentile of maximum daily 8 h average (MDA8) O3 in the YRD region reached 158 μ g / m 3 in 2023 (China Environment Report 2023, available at https://www.mee.gov.cn/hjzl/sthjzk/zghjzkgb/, accessed on 20 August 2024), which far exceeds the World Health Organization’s threshold (100 μ g / m 3 ). Given the high O3 levels in the YRD region, it is necessary to monitor tropospheric O3 and its precursors in the YRD region for diagnosing O3 formation mechanisms.
As a hyper-spectral remote sensing technique, MAX-DOAS [24,25] has the advantages of high sensitivity, strong stability, and high portability and has been widely applied in air pollution monitoring. The MAX-DOAS instrument can measure the solar spectra at different elevation angles to retrieve profiles of trace gases and aerosols based on the DOAS and the optimal estimation method (OEM) [26,27,28,29]. In recent decades, the MAX-DOAS technique has been widely applied to retrieve HCHO and NO2 profiles and analyze O3 formation sensitivity [30,31,32,33].
However, due to the difficulties in separating stratospheric O3 absorption, few studies have analyzed O3 formation sensitivity using synchronous MAX-DOAS NO2, HCHO, and O3 measurements at different atmospheric layers. Recently, we developed a new profile retrieval algorithm to calculate tropospheric O3 profiles using MAX-DOAS measurements, where the stratospheric O3 profiles from microwave limb sounder (MLS) were used to simulate stratospheric O3 absorption in the SCIATRAN model [34]. In this study, our aim is to use the MAX-DOAS measurements from Hefei to retrieve synchronous NO2, HCHO, and O3 profiles to diagnose O3 sensitivity at different layers. Herein, the regime transitions of O3 formation sensitivity were derived using third-order polynomial models between HCHO/NO2 ratios and O3, thus calculating the contributions of different regimes at different layers. The results of this study will help us understand the tropospheric O3 formation mechanisms in the YRD region.

2. Measurement and Method

2.1. MAX-DOAS Measurement

Ground-based MAX-DOAS measurements were implemented to diagnose O3 formation sensitivity in Hefei, China, from July to October 2023. The MAX-DOAS instrument was manufactured by Anhui Institute of Optics and Fine Mechanics (AIOFM), which is primarily composed of an optical fiber, a telescope, a prism, a computer, a motor, a temperature control system, and a UV spectrometer. The MAX-DOAS instrument was installed on the roof of a 5-storey building (approximately 15 m) at the AIOFM site (31.90°N, 117.18°E) in urban Hefei (Figure 1). The AIOFM site is approximately 15 km away from Hefei City Center. The full measurement sequence consists of 2°, 3°, 4°, 5°, 6°, 8°, 10°, 15°, 30°, and 90°, with an azimuth angle of 0°. The MAX-DOAS instrument at the AIOFM site collects scattered solar spectra between 290 and 420 nm.

2.2. Auxiliary Data

The CNEMC network (https://www.cnemc.cn), established by the Chinese government, primarily monitors six air pollutants (O3, NO2, CO, SO2, PM2.5, and PM10) in 454 cities using ultraviolet fluorescence, a spectrometer, infrared absorption, and the chemiluminescence method [35,36]. The in situ NO2 and O3 measurements from the CNEMC site (ID: 1273A) were used to validate retrieved surface results from MAX-DOAS measurements. The distance between 1273A and the AIOFM site is less than 3 km.
The TROPOspheric monitoring instrument (TROPOMI) onboard the Sentinel-5P satellite was launched in 2017, with an overpass time and spatial resolution of 13:30 local time (LT) and 3.5 × 7 km2, respectively [37,38]. Herein, the offline stratospheric O3 profiles, tropospheric HCHO, and NO2 vertical column densities (VCDs) were derived from TROPOMI (https://disc.gsfc.nasa.gov/). Meanwhile, the cloudy pixel data (cloud fraction > 0.3) of the TROPOMI results were removed to reduce the deviations from the cloud. The average TROPOMI HCHO and NO2 VCDs used in this study were calculated within a grid of 0.1° near the AIOFM site, and the grid for stratospheric O3 profiles was 1.0°.

2.3. Profiles Retrieval

The differential slant column densities (DSCDs) of trace gases can be retrieved using the QDOAS software (http://uv-vis.aeronomie.be/software/QDOAS/, accessed on 20 October 2020) and measured spectra using the DOAS method [28], which can be found in Text S1 of the Supplementary File. The parameters for retrieving NO2, HCHO, O3, and O4 DSCDs are listed in Table S1, with the Fraunhofer reference spectrum of the sequential zenith spectrum. An example of spectral fitting (elevation angle of 2°, 15 July 2023 at 08:58 LT) is shown in Figure S1. The retrieved NO2, HCHO, O3, and O4 DSCDs are 4.92 ± 0.12 × 1016, 4.71 ± 0.58 × 1016, 7.79 ± 0.29 × 1017, and 2.25 ± 0.05 × 1043 molec/cm2, respectively, with remaining residuals of 6.99 × 10−4, 6.94 × 10−4, 7.83 × 10−4, and 6.98 × 10−4, respectively.
Herein, the two-step Heidelberg profile (HEIPRO) algorithm [26,39] derived from OEM [40] was used to retrieve aerosol, NO2, HCHO, and O3 profiles using the forward SCIATRAN model [41]. First, aerosol profiles were retrieved using the calculated O4 DSCDs at different elevation angles. Then, the NO2, HCHO, and O3 profiles were retrieved using corresponding DSCDs and aerosol profiles. For the retrieval of O3 profiles, tropospheric DSCDs (DSCDstrop, calculated by eliminating the stratospheric O3 absorption) were used instead of the DSCDs from the QDOAS software, as described in our previous study [34]. The profiles were retrieved by minimizing the cost function of χ 2 :
χ 2 x = F x − y T S ε − 1 F x − y + x − x a T S a − 1 x − x a
Here, x and F x denote the state vector and forward model, respectively, y and x a denote the calculated DSCDs and the a priori state vector, respectively, and S ε and S a denote the error matrices of y and x a , respectively.
For NO2 and HCHO retrieval, the vertical resolution was set to 100 m at 0–1 km and 200 m at 1–3 km; for O3 retrieval, a fixed vertical resolution of 100 m was set. Exponentially decreasing a priori profiles were used with surface NO2, HCHO, and O3 of 1, 1, and 10 ppb. In the HEIPRO algorithm, a fixed temporal resolution of 15 min (approximately two sequences) was set, with a correlation length of 0.5 km. Typical average kernels for retrieving profiles of aerosols, NO2, HCHO, and O3 are shown in Figure S2, with the degrees of freedoms (DOFs) of 2.41, 3.93, 2.53, and 3.61, respectively. Overall, the retrieved profiles are relatively sensitive to the true states at 0–1 km, whereas decreased sensitivity was observed in elevated layers. In addition, the linear regression analyses between measured and simulated DSCDs of NO2, HCHO, and O3 on 15 July 2023 are shown in Figure S3. The correlation coefficients (R) are 0.99, 0.98, and 0.96, indicating that the DSCDs can be reproduced well using the HEIPRO algorithm.

3. Results and Discussions

3.1. Diurnal Variations of NO2, HCHO, and O3

Diurnal variations of PBL NO2 at AIOFM site are shown in Figure 2. Overall, NO2 pollution episodes mainly occurred in lower PBL (0–500 m), which indicates that NO2 pollution at the AIOFM site was mainly caused by near-surface anthropogenic emissions. High NO2 values appeared on 4, 16, and 24 August and on 9, 10, and 28 September with a peak of approximately 30 ppb located at 0–300 m. In addition, enhanced NO2 occurred at the surface during 08:00–10:00 LT and then gradually decreased with photolysis. The lower PBL NO2 of the AIOFM site fluctuated from 0.11 to 33.56 ppb with an average of 3.15 ppb.
Diurnal HCHO variations at the AIOFM site are shown in Figure 3. Overall, HCHO pollution episodes of the AIOFM site mainly occurred in the lower PBL, indicating that HCHO pollution was also caused by near-surface anthropogenic emissions. The lower PBL HCHO of the AIOFM site fluctuated from 0.91 to 24.42 ppb, with an average of 7.24 ppb. High HCHO values appeared on 4 and 5 August and on 9 and 10 September, with a peak of approximately 25 ppb located at 300–500 m. Enhanced HCHO mainly appeared at 300–500 m instead of the surface, indicating that the oxidation of VOCs mainly occurred in elevated layers. The daily HCHO concentrations were significantly higher than those of NO2, which was mainly due to the decreased NO2 lifetime and increased HCHO abundance caused by stronger photochemical reactions.
To reduce the impact of meteorological factors, the measured spectra from 12:00 to 17:00 LT were used to retrieved the O3 profiles, when the sunlight-driven photochemical reactions producing O3 were stronger. The vertical O3 profiles at the AIOFM site retrieved from MAX-DOAS measurements are shown in Figure 4. Overall, enhanced O3 at the AIOFM site mainly occurred at 0–1 km above the surface. The daily maximum O3 level was mainly located at 300–500 m, which may be attributed to the stronger photochemical reactions in elevated layers. The O3 in the lower PBL fluctuated from 18.01 to 170.73 ppb, with an average of 74.02 ppb. As shown in Figure 4, severe O3 pollution appeared from 10 to 26 August 2023 and gradually eased in early September.

3.2. Validations

The average hourly surface NO2 and O3 (0–100 m) at the AIOFM site from MAX-DOAS measurements were validated using in situ measurements from the CNEMC network (Figure 5). Overall, retrieved surface NO2 and O3 are well correlated with that from CNEMC, with R values of 0.81 and 0.80, respectively. The retrieved surface O3 fluctuated between 56.30 and 237.88 μ g / m 3 , with an average of 119.16 ± 38.19 μ g / m 3 , which exceeds the National Grade I standard (100 μ g / m 3 ). It should be noted that surface HCHO results using the HEIPRO algorithm were validated with the in situ 2,4-dinitrophenylhydrazine technique in our previous study [19].
The average daily MAX-DOAS NO2 and HCHO VCDs were calculated using the integrations of retrieved profiles from 13:00 to 14:00 LT and were compared with the TROPOMI results (Figure 6). Overall, the MAX-DOAS NO2 and HCHO VCDs are well correlated with those from TROPOMI, with R values of 0.81 and 0.77, respectively.
However, TROPOMI VCDs showed an underestimation effect compared to MAX-DOAS VCDs, which is attributable to the wide-area averaging effect of TROPOMI pixels [42]. In addition, TROPOMI has a lower sensitivity for retrieving the tropospheric trace gases than the MAX-DOAS measurements [33]. This underestimation effect is similar to the results of previous studies. For example, Griffin et al. [43] validated TROPOMI tropospheric NO2 VCDs using Pandora DOAS measurements (slope = 0.69, R = 0.70), and De Smedt et al. [44] compared TROPOMI tropospheric HCHO columns using the MAX-DOAS measurements from 18 stations (slope = 0.60, R = 0.76).

3.3. Diagnosis of O3 Formation Sensitivity

The HCHO/NO2 ratios can be used as indicators to diagnose O3-VOC-NOx sensitivity [19,21,31]. Generally, PBL O3 is formed under a VOC-limited regime with low HCHO/NO2 ratios, whereas under a NOx-limited regime, it formed with high HCHO/NO2 ratios. Herein, the regime transition (VOC-NOx-limited regime with intermediate HCHO/NO2 ratios) of O3 formation sensitivity was derived using the retrieved vertical profiles of HCHO/NO2 ratios, and O3. Hong et al. [31] and Jin et al. [45] calculated the regime transitions by fitting HCHO/NO2 ratios and increased O3 (ΔO3, differences between daytime O3 and nighttime O3) with third-order polynomial models. However, it is difficult to determine ΔO3 using MAX-DOAS measurements. Fortunately, recent studies have demonstrated that the O3 formation rates can be substituted for O3 abundances [46,47,48]. Therefore, the fitting curves between the HCHO/NO2 ratios and O3 were used to calculate the regime transitions in this study. The maximum of the fitting curves denotes the transition from the VOC-limited to NOx-limited regimes, and the HCHO/NO2 ratios spanning 10% of high O3 denote the regime transition.
The consistency of O3 formation sensitivity between surface HCHO/NO2 ratios and daily average O3 (or hourly average ΔO3) was analyzed. The surface-layer fitting curve between HCHO/NO2 ratios and daily average O3 (or hourly average ΔO3) is shown in Figure 7a (Figure 7b), with R values of 0.69 and 0.72, respectively. Overall, the third-order models achieved a good estimation of the relationship between O3 (or ΔO3) and HCHO/NO2 ratios, with 91.4% and 94.4% of the data falling within the 95% prediction interval (red area). The calculated regime transition of this study (Figure 7a) ranged from 2.21 to 2.46, with a peak of 2.33, which is similar to the regime transition (ranging from 2.39 to 2.71 with a peak of 2.55) calculated using HCHO/NO2 ratios and ΔO3 (Figure 7b). Therefore, the surface-layer O3 formation sensitivity ranged from the VOC-limited (0 < HCHO/NO2 ratios < 2.21) to VOC-NOx-limited (2.21 < HCHO/NO2 ratios < 2.46) to NOx-limited (HCHO/NO2 ratios > 2.46) regimes.
Based on the above definitions, the regime transitions and corresponding fitted polynomials were calculated at different layers (Table S2). The regime transitions at 0–300 m are shown in Figure S4, with R values of 0.69, 0.67, and 0.66, respectively. The binned statistics of HCHO/NO2 ratios and corresponding regime transitions at different layers are shown in Figure 8, with the top and bottom of the box representing the 75th and 25th percentiles, respectively. The red line and blue shaded area denote the average HCHO/NO2 ratios and calculated regime transitions, respectively. The average HCHO/NO2 ratio has a peak of 4.28 in the 500–600 m layer, and the maximum thresholds of regime transitions are located at 700–800 m. Overall, the O3 formation is mainly dominated by the VOC-limited regime in the lowest 0–1 km with a contribution of 74.19%, whereas 7.33% and 18.48% for the VOC-NOx-limited and NOx-limited regimes, respectively, which corresponds with Hong et al. (67.5% for the VOC-limited regime, 17.6% for the VOC-NOx-limited regime, and 14.9% for the NOx-limited regimes) and Hu et al. (69.2% for the VOC-limited regime, 10.2% for the VOC-NOx-limited regime, and 20.6% for the NOx-limited regimes) [31,46]. The detailed contributions of O3 formation sensitivity at different layers are listed in Table S2.

3.4. O3 Pollution Analyses

In this study, the MDA8 O3 level was used to distinguish between non-polluted (<160 μ g / m 3 ) and polluted days ( ≥ 160 μ g / m 3 ). The average diurnal variations in O3, HCHO, NO2, and HCHO/NO2 ratios on non-polluted and polluted days are shown in Figure 9. Overall, enhanced O3 and HCHO mainly appeared in lower PBL, while enhanced NO2 mainly appeared below 300 m. From non-polluted to polluted days, an average increase of 49.88% appeared in lower PBL O3 concentrations, whereas the maximum increase (72.56%) appeared at 200–300 m. Meanwhile, the concentrations of HCHO and NO2 in the lower PBL increased by 77.26% and 45.75%, respectively, during the polluted days, which led to a 27.77% increase in HCHO/NO2 ratios in the lower PBL. In other words, elevated HCHO and NO2 levels promoted the formation of O3 in the lower PBL. During non-polluted days, the average contributions of the VOC-limited, VOC-NOx-limited, and NOx-limited regimes in the lower PBL are 69.46%, 8.73%, and 21.81%, respectively, and 56.08%, 9.96%, and 33.96%, respectively, on polluted days. At 0–300 m, the average contributions of the NOx-limited regime increased from 13.15% on non-polluted days to 26.83% on polluted days, whereas it increased from 30.47% to 45.28% at 300–600 m. Consequently, the contributions of the NOx-limited regime increased significantly at the higher layers of polluted days, which corresponds with a recent study by Hu et al. [46].
A typical O3 pollution process divided into three episodes (before pollution from 31 August to 2 September, during pollution on 3–5 September, and after pollution on 7–9 September) is shown in Figure 10, with the averaged lower PBL O3 concentrations of 61.86, 81.78, and 62.25 ppb, respectively. For the before and after pollution episodes, daily average O3 and HCHO in the lower PBL are less than 67 and 9 ppb, whereas high O3 (81.78 ppb) and HCHO (11.75 ppb) episodes appeared during the pollution episode, which contribute to the high HCHO/NO2 ratios in the lower PBL. The averaged lower PBL HCHO/NO2 ratios before, during, and after pollution are 2.39, 3.89, and 3.12, respectively. Based on the definition in Table S2, the average contributions of the VOC-limited, VOC-NOx-limited, and NOx-limited regimes in the lower PBL are 84.72% (58.33%), 7.50% (26.67%), and 7.78% (15.00%) before (and after) pollution and 39.17%, 20.00%, and 40.83% during pollution. In the lower PBL, the contributions of the NOx-limited regime increased from 4.44–38.89% (whole episode) to 16.67–68.33% (during pollution), whereas VOC-NOx-limited increased from 3.88–23.33% to 11.67–31.67%. At 0–300 m, the average contribution of the NOx-limited regime increased from 11.67% (whole episode) to 26.67% (during pollution), whereas that of the VOC-limited regime decreased from 76.85% to 56.11%. At 300–600 m, the average contribution of NOx-limited regime increased from 30.74% (whole episode) to 55.56% (during pollution), whereas that of the VOC-limited regime decreased from 44.63% to 22.78%. Therefore, this O3 pollution episode is mainly dominated by the VOC-limited regime in surface layers and the NOx-limited regime in elevated layers.

4. Summary

Synchronous NO2, HCHO, and O3 profiles were retrieved from MAX-DOAS measurements. The retrieved hourly average surface NO2 and O3 concentrations were validated with CNEMC in situ measurements, with R values of 0.81 and 0.80, respectively. In addition, daily NO2 and HCHO VCDs from MAX-DOAS were compared with TROPOMI, with R values of 0.81 and 0.77, respectively. Enhanced NO2 mainly occurred at the surface, whereas enhanced HCHO mainly occurred at 300–500 m, indicating the oxidation of VOCs mainly occurred in elevated layers. Enhanced O3 was mainly located at 300–500 m, which can be attributed to the stronger photochemical reactions in elevated layers.
The regime transitions of O3 formation sensitivity at different layers were then calculated using the fitting curves between HCHO/NO2 ratios and O3, with the surface regime transition of 2.21–2.46, which is similar to the regime transition (ranging from 2.39 to 2.71) between HCHO/NO2 ratios and ΔO3. Based on the calculated regime transitions, the contributions of the VOC-limited, VOC-NOx-limited, and NOx-limited regimes during the observation period are 74.19%, 7.33%, and 18.48%, respectively. Therefore, stricter VOC emission restriction strategies should be formulated compared with those for reducing NOx emissions in the YRD region. In addition, the O3 formation sensitivity on polluted and non-polluted days was analyzed. On non-polluted days, the contributions of the VOC-limited regime were predominant, whereas those of the NOx-limited regime were predominant in the elevated layers during polluted days. Moreover, a typical O3 pollution episode dominated by the VOC-limited regime was analyzed. The average contributions of the VOC-limited regime before, during, and after pollution are 84.72%, 39.17%, and 58.33%, respectively. At 0–300 m, the average contributions of the NOx-limited regime increased from 11.67% (whole episode) to 26.67% (during pollution), whereas it increased from 30.74% to 55.56% at 300–600 m, indicating that the NOx-limited regime was predominant in elevated layers during polluted days. The results of this study will help us understand the tropospheric O3 formation mechanisms and formulate O3 mitigation strategies in the YRD region.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/rs17040658/s1. Table S1. The detailed parameters of DOAS fitting for O4, NO2, and HCHO. Table S2. The detailed regime transitions and contributions of the VOC-limited, NOx-limited, and VOC-NOx-limited regimes at lowest 1 km. Figure S1. An example of a typical spectral fitting. Figure S2. The typical averaging kernels of aerosol (a) NO2 (b), HCHO (c), and O3 (d) retrievals. Figure S3. Linear regression analyses between measured and simulated DSCDs of NO2 (a), HCHO (b), and O3 (c). Figure S4. Regime transitions of 0–0.1 km (a), 0.1–0.2 km (b), and 0.2–0.3 km (c). Figure S5. Regime transitions of mid-layer (0.4–0.5 km, left panel) and top-layer (0.9–1.0 km, right panel). References [49,50,51,52,53] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, Y.Q., D.W., Z.L., G.Y., F.S., and Y.L.; methodology, Y.Q., D.W., and Z.L.; software, Y.Q., G.Y., M.Z., and H.Z.; validation, Y.Q., G.Y., and F.S.; formal analysis, Y.Q. and Y.L.; investigation, Y.Q. and G.Y.; resources, Y.Q., F.S., and Y.L.; writing—original draft preparation, Y.Q.; writing—review and editing, Y.L. and F.S.; visualization, Y.Q. and G.Y.; supervision, Y.L. and F.S.; project administration, Y.Q.; funding acquisition, Y.Q. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by Anhui Provincial Natural Science Foundation (Grant No. 2408085QD114), Dreams Foundation of Jianghuai Advanced Technology Center (Grant No. 2023-ZM01K006), and National Key Research and Development Program of China (Grant No. 2022YFB3904805).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We gratefully acknowledge IUP Heidelberg University for providing the HEIPRO algorithm and BIRA-IASB for providing the QDOAS software. The authors gratefully acknowledge NASA for providing the TROPOMI datasets and University of Bremen for providing the SCIATRAN model.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Multi-axis differential optical absorption spectroscopy (MAX-DOAS) instrument and the measurement site.
Figure 1. Multi-axis differential optical absorption spectroscopy (MAX-DOAS) instrument and the measurement site.
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Figure 2. Diurnal variations of NO2 at the AIOFM site from MAX-DOAS measurements.
Figure 2. Diurnal variations of NO2 at the AIOFM site from MAX-DOAS measurements.
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Figure 3. Diurnal variations of HCHO at the AIOFM site from MAX-DOAS measurements.
Figure 3. Diurnal variations of HCHO at the AIOFM site from MAX-DOAS measurements.
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Figure 4. Vertical O3 profiles at the AIOFM site from MAX-DOAS measurements.
Figure 4. Vertical O3 profiles at the AIOFM site from MAX-DOAS measurements.
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Figure 5. Linear fittings of surface NO2 (a) and O3 (b) between CNEMC in situ and MAX-DOAS measurements.
Figure 5. Linear fittings of surface NO2 (a) and O3 (b) between CNEMC in situ and MAX-DOAS measurements.
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Figure 6. Linear fittings of tropospheric NO2 (a) and HCHO (b) VCDs between MAX-DOAS and TROPOMI measurements.
Figure 6. Linear fittings of tropospheric NO2 (a) and HCHO (b) VCDs between MAX-DOAS and TROPOMI measurements.
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Figure 7. (a) Third-order fitting curve between surface HCHO/NO2 ratios and O3; (b) third-order fitting curve between surface HCHO/NO2 ratios and ΔO3. The red and blue areas denote the 95% prediction interval and regime transition, respectively. The red and blue lines denote the fitting curve and the peak of the fitting curve, respectively.
Figure 7. (a) Third-order fitting curve between surface HCHO/NO2 ratios and O3; (b) third-order fitting curve between surface HCHO/NO2 ratios and ΔO3. The red and blue areas denote the 95% prediction interval and regime transition, respectively. The red and blue lines denote the fitting curve and the peak of the fitting curve, respectively.
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Figure 8. The regime transitions (blue shaded area), binned statistics of HCHO/NO2 ratios (boxes), averaged values (triangles), and the calculated HCHO/NO2 profile (red line).
Figure 8. The regime transitions (blue shaded area), binned statistics of HCHO/NO2 ratios (boxes), averaged values (triangles), and the calculated HCHO/NO2 profile (red line).
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Figure 9. Average diurnal variations of O3, HCHO, NO2, and HCHO/NO2 ratios on non-polluted (a) and polluted days (b).
Figure 9. Average diurnal variations of O3, HCHO, NO2, and HCHO/NO2 ratios on non-polluted (a) and polluted days (b).
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Figure 10. Diurnal variations of O3 (a), HCHO (b), NO2 (c), and HCHO/NO2 ratios (d) in a typical O3 pollution episode.
Figure 10. Diurnal variations of O3 (a), HCHO (b), NO2 (c), and HCHO/NO2 ratios (d) in a typical O3 pollution episode.
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Qian, Y.; Wang, D.; Li, Z.; Yan, G.; Zhao, M.; Zhou, H.; Si, F.; Luo, Y. Ground-Based MAX-DOAS Observations of Tropospheric Ozone and Its Precursors for Diagnosing Ozone Formation Sensitivity. Remote Sens. 2025, 17, 658. https://doi.org/10.3390/rs17040658

AMA Style

Qian Y, Wang D, Li Z, Yan G, Zhao M, Zhou H, Si F, Luo Y. Ground-Based MAX-DOAS Observations of Tropospheric Ozone and Its Precursors for Diagnosing Ozone Formation Sensitivity. Remote Sensing. 2025; 17(4):658. https://doi.org/10.3390/rs17040658

Chicago/Turabian Style

Qian, Yuanyuan, Dan Wang, Zhiyan Li, Ge Yan, Minjie Zhao, Haijin Zhou, Fuqi Si, and Yuhan Luo. 2025. "Ground-Based MAX-DOAS Observations of Tropospheric Ozone and Its Precursors for Diagnosing Ozone Formation Sensitivity" Remote Sensing 17, no. 4: 658. https://doi.org/10.3390/rs17040658

APA Style

Qian, Y., Wang, D., Li, Z., Yan, G., Zhao, M., Zhou, H., Si, F., & Luo, Y. (2025). Ground-Based MAX-DOAS Observations of Tropospheric Ozone and Its Precursors for Diagnosing Ozone Formation Sensitivity. Remote Sensing, 17(4), 658. https://doi.org/10.3390/rs17040658

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