Meteorological and chemical controls on surface ozone diurnal variability in Beijing: A clustering-based perspective

Liao, Zhiheng; Pan, Yubing; Peng, Ming; Jia, Xingcan; Zou, Cheng; Wang, Qianqian; Dou, Youjun; Zhao, Xiujuan; Quan, Jiannong

doi:10.1016/j.atmosenv.2022.119566

Cited by 10 publications

(3 citation statements)

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“…Figure 5 shows satellite-derived gapless surface O3 μg/m³). This difference is primarily ascribed to the complex interplay of various atmospheric processes, emissions, and photochemical reactions, e.g., higher oxidant OX (O3 and NO2) levels during the daytime (S. Han et al, 2011) and lower nighttime boundary layer height facilitating NO titration reactions that deplete nighttime O3 (Liao et al, 2023). Similar diurnal variations in surface O3 are observed at regional scales, with the highest values typically occurring around 15:00 LT (Figure 7).…”

Section: Diurnal Variations In Surface O3 and Driving Factorsmentioning

confidence: 84%

First retrieval of 24-hourly 1-km-resolution gapless surface ozone (O 3) from space in China using artificial intelligence: diurnal variations and implications for air quality and phytotoxicity

Cheng,

Li,

Yang

et al. 2024

Preprint

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Surface ozone (O3) is a crucial ambient pollutant gas that poses substantial risks to both human health and ecosystems. Nonetheless, there is a scarcity of high-spatial-resolution hourly surface O3 data, particularly during the day when this information is needed due to the strong diurnal variations of O3. We thus determined a best-performing artificial intelligence model to derive 24-hourly 1-kmresolution surface O3 concentrations in China from a large array of satellite and surface data, which can portray well the diurnal variations of O3 concentration. The overall sample-based crossvalidated coefficients of determination (root-mean-square error) are 0.89 (15.74 μg/m 3 ), 0.91 (14.91 μg/m 3 ), and 0.85 (16.31 μg/m 3 ) during the full day (00:00-23:00 local time, or LT), daytime (08:00-17:00 LT), and nighttime (18:00-07:00 LT), respectively. The surface O3 level generally rises from sunrise, around 07:00 LT, reaching a peak at ~15:00 LT, then continuously declining overnight. The magnitude of the diurnal variation amounts to 180% relative to its diurnal mean level. During daytime, solar radiation in the ultraviolet and shortwave spectral bands, along with temperature, explain more than half (32% and 24%) of the diurnal variations using the interpretable SHapley Additive exPlanations (SHAP) method, while nighttime O3 levels are dominated by temperature (31%) and relative humidity (16%). In 2018, approximately 59%, 93%, and 100% of populated areas were susceptible to O3 exposure risk for at least one day, with the maximum daily average 8-h O3 levels surpassing the World Health Organization's recommended daily air quality standards of 160 µg/m³, 120 µg/m³, and 100 µg/m³, respectively. Approximately 65%, 70%, and 99% of vegetated areas in China exceed the minimum critical levels for O3 mixing ratios, as determined by the sum of all hourly values ≥ 0.06 μmol mol -1 (SUM06), the sigmoidally weighted sum of all hourly values (W126), and accumulates over the threshold of 40 nmol mol -1 (AOT40), respectively. Notably, gross primary productivity stands out as the most responsive indicator to surface O3 pollution across various vegetated types in China, especially concerning the Hourly O3 Accumulates without Threshold (AOT0, R = -0.37--0.53, p < 0.001).

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Section: Diurnal Variations In Surface O3 and Driving Factorsmentioning

confidence: 84%

First retrieval of 24-hourly 1-km-resolution gapless surface ozone (O 3) from space in China using artificial intelligence: diurnal variations and implications for air quality and phytotoxicity

Cheng,

Li,

Yang

et al. 2024

Preprint

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“…In summer, northern China is controlled by a continental thermal low-pressure system with prevailing southerly flows in the North China Plain. The southerly flows are favourable for transporting ozone and its precursors from central eastern China to Beijing (Liao et al, 2023), resulting in ozone production and accumulation in the presence of strong ultraviolet radiation. From the FTO 3 -dominated to MLO 3 -dominated patterns, the low-pressure system is gradually weakened.…”

Section: Meteorological Interpretationsmentioning

confidence: 99%

Mixing-layer-height-referenced ozone vertical distribution in the lower troposphere of Chinese megacities: stratification, classification, and meteorological and photochemical mechanisms

Liao,

Gao,

Zhang

et al. 2024

Atmos. Chem. Phys.

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Abstract. Traditional tropospheric ozone (O3) climatology uses a simple average substantially smoothed stratification structure in individual O3 profiles, limiting our ability to properly describe and understand how O3 is vertically distributed at the interface between the mixing layer (ML) and free troposphere (FT). In this study, we collected 1897 ozonesonde profiles from two Chinese megacities (Beijing and Hong Kong) over the period 2000–2022 to investigate the climatological vertical heterogeneity of the lower-tropospheric O3 distribution with a mixing-layer-height-referenced (h-referenced) vertical coordinate system. The mixing-layer height (h) was first estimated following an integral method that integrates the information of temperature, humidity, and cloud. After that, a so-called h-referenced vertical distribution of O3 was determined by averaging all individual profiles expressed as a function of z/h rather than z (where z is altitude). We found that the vertical stratification of O3 is distributed heterogeneously in the lower troposphere, with stronger vertical gradients at the surface layer and ML–FT interface. There are low vertical autocorrelations of O3 between the ML and FT but high autocorrelations within each of the two atmospheric compartments. These results suggest that the ML–FT interface acts as a geophysical “barrier” separating air masses of distinct O3 loadings. This barrier effect varies with season and city, with an ML–FT detrainment barrier in summer (autumn) and an FT–ML entrainment barrier in other seasons in Beijing (Hong Kong). Based on a Student's t test, daily h-referenced O3 profiles were further classified into three typical patterns: MLO3-dominated, FTO3-dominated, and uniform distribution. Although the FTO3-dominated pattern occurs most frequently during the whole study period (69 % and 54 % of days in Beijing and Hong Kong, respectively), the MLO3-dominated pattern prevails in the photochemically active season, accounting for 47 % of summer days in Beijing and 54 % of autumn days in Hong Kong. These occurrences of the MLO3-dominated pattern are significantly more frequent than in previously reported results at northern mid-latitudes, indicating intensive photochemical MLO3 production under the high-emission background of a Chinese megacity. From a FTO3-dominated to MLO3-dominated pattern, the O3 precursor CH2O (NO2) experiences a substantial increase (decrease) in Beijing but a slight change in Hong Kong. Vertically, the increment of CH2O is larger in the upper ML, and the decrement of NO2 is larger in the lower ML. Such vertical changes in O3 precursors push O3 production sensitivity away from the VOC-limited regime and facilitate high-efficiency production of O3 via photochemical reactions, particularly in the upper ML of Beijing.

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“…This ozonesonde dataset is also a unique, available, in situ ozone measurement dataset that reveals the long-term variations in tropospheric and stratospheric ozone on the North China Plain, particularly around the Beijing region [30]. Previous studies using ozonesonde measurements over Beijing primarily focused on the vertical characteristics of climatological ozone and its variation (e.g., [7,[31][32][33][34]); however, the dominant modes of ozone column variability and the driving factors (such as the ENSO, QBO, and 11-year solar activity cycle) of local ozone variation have not been well discussed from the perspective of time series analysis. Based on the above considerations, we first apply wavelet analysis to ozonesonde measurements in Beijing during 2001-2019 to explore the dominant modes of ozone variability over Beijing, and preliminarily discuss the driving factors (including the ENSO, QBO, and 11-year solar activity cycle) of ozone variability.…”

Section: Introductionmentioning

confidence: 99%

Wavelet Analysis of Ozone Driving Factors Based on ~20 Years of Ozonesonde Measurements in Beijing

Zeng,

Zhang,

et al. 2023

Atmosphere

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A long-term vertical ozone observational dataset has been provided during 2001–2019 by ozonesonde measurements in Beijing on the North China Plain. Previous studies using this dataset primarily focused on the vertical characteristics of climatological ozone and its variation; however, the driving factors of ozone variation have not been well discussed. In this study, by applying the wavelet analysis method (including continuous wavelet transform and cross wavelet) and sliding correlation coefficients to ~20 years of ozonesonde measurements collected in Beijing, we analyzed the dominant modes of ozone column variability within three height ranges over Beijing (total column ozone: TOT; stratospheric column ozone: SCO; and tropospheric column ozone: TCO). Moreover, we also preliminarily discussed the relationship between these three ozone columns and the El Niño Southern Oscillation (ENSO), Quasi-biennial Oscillation (QBO), and 11-year solar activity cycle. The results revealed that the ozone columns within the three height ranges predominantly adhered to interannual variability patterns, and the short-term variabilities in TOT and SCO may have been related to eruptive volcanic activity. In comparison to the TOT and SCO, the TCO was more susceptible to the forcing influences of high-frequency factors such as pollutant transport. Similar to the results in other mid-latitude regions, strong ENSO and QBO signals were revealed in the interannual ozone column variability over Beijing. The TOT and SCO showed positive anomalous responses to ENSO warm-phase events, and the peak of the ENSO warm phase led the winter peaks of the TOT and SCO by approximately 3–6 months. During the strong cold–warm transition phase in 2009–2012, the TOT and SCO showed a significant positive correlation with the ENSO index. The strong seasonality of the meridional circulation process driven by the QBO led to a significant positive correlation between the QBO index and the TOT and SCO in the interannual cycle, except for two periods of abnormal QBO fluctuations in 2010–2012 and 2015–2017, whereas the TCO showed a time-lagged correlation of approximately 3 months in the annual cycle relative to the QBO due to the influence of the thermodynamic tropopause. In addition, analysis of the F10.7 index and the ozone columns revealed that the ozone columns over Beijing exhibited lagged responses to the peaks of sunspot activity, and there was no obvious correlation between ozone columns and 11-year solar activity cycle. Given the complex driving mechanism of the climatic factors on local ozone variability, the preliminary results obtained in this study still require further validation using longer time series of observational data and the combination of chemical models and more auxiliary data.

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Meteorological and chemical controls on surface ozone diurnal variability in Beijing: A clustering-based perspective

Cited by 10 publications

References 50 publications

First retrieval of 24-hourly 1-km-resolution gapless surface ozone (O 3) from space in China using artificial intelligence: diurnal variations and implications for air quality and phytotoxicity

First retrieval of 24-hourly 1-km-resolution gapless surface ozone (O 3) from space in China using artificial intelligence: diurnal variations and implications for air quality and phytotoxicity

Mixing-layer-height-referenced ozone vertical distribution in the lower troposphere of Chinese megacities: stratification, classification, and meteorological and photochemical mechanisms

Wavelet Analysis of Ozone Driving Factors Based on ~20 Years of Ozonesonde Measurements in Beijing

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