Near-surface Ozone Concentrations Research Articles

Estimation of Near-Surface High Spatiotemporal Resolution Ozone Concentration in China Using Himawari-8 AOD

Near-surface ozone is a secondary pollutant, and its high concentrations pose significant risks to human and plant health. Based on an Extra Tree (ET) model, this study estimated near-surface ozone concentrations with the high spatiotemporal resolution based on Himawari-8 aerosol optical depth (AOD) data and meteorological variables from 1 January 2016 to 31 December 2020. The SHapley Additive exPlanation (SHAP) method was employed to evaluate the contribution of AOD and meteorological factors on ozone concentration. The results indicate that (1) the ET model achieves a sample-based cross-validation R2 of 0.75–0.87 and an RMSE (μg/m3) of 17.96–20.30. The coefficient of determination (R2) values of the model in spring, summer, autumn, and winter are 0.81, 0.80, 0.87, and 0.75, respectively. (2) Higher temperature and boundary layer heights were found to positively contribute to ozone concentration, whereas higher relative humidity exerted a negative influence. (3) From 11:00 to 15:00 (Beijing time, UTC+08:00), ozone concentration increases gradually, with the highest occurring in the summer, followed by spring. This study has obtained high spatial and temporal resolution ozone concentration data, offering valuable insights for the development of fine-scale ozone pollution prevention and control strategies.

Tropospheric ozone precursors: global and regional distributions, trends, and variability

Abstract. Tropospheric ozone results from in situ chemical formation and stratosphere–troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

Diurnal hourly near-surface ozone concentration derived from geostationary satellite in China

Near-surface O3 is a harmful atmospheric pollutant and a key component of urban photochemical pollution. The availability of satellite ozone concentration products is predominantly restricted to daytime, resulting in a lack of understanding of nighttime ozone pollution (e.g. nocturnal ozone enhancement events). This research leverages 5-km bright temperatures derived from Advanced Himawari Images (AHI) on the Himawari-8 satellite, in conjunction with auxiliary data, to estimate 24-h near-surface O3 concentrations in China at a resolution of 5km for 2020. The model achieves an average 5-fold cross-validation R2 of 0.92. Comparative analysis with on-site observations reveals that the model has low relative errors between 8:00 and 21:00 LT. The estimated O3 maps depict a consistent 24-h variation pattern, characterized by high and most fluctuating concentrations during the daytime, reaching a peak around 16:00 LT, which is primarily due to the increased photochemical reactions and the O3 accumulation in the mid-afternoon. In the daytime of summer, high surface ozone concentrations are mainly contributed by June. The elevated levels of O3 are predominantly found in central China, particularly in the Beijing-Tianjin-Hebei region and Inner Mongolia. It can also be seen that although the highest average daytime surface O3 concentration occurs in summer, the highest nighttime concentration is observed in spring, which may be attributed to the frequent occurrence of horizontal transport and vertical mixing of O3. This study holds promise in providing comprehensive round-the-clock surface O3 data across China, thereby enhancing our understanding of diurnal ground-level O3 variations.

Near-surface ozone concentration variability analysis in the Karadag Nature Reserve

The article presents the results of a study of a near-surface ozone concentration variability in the Crimea at the background environmental monitoring station in the Karadag Nature Reserve for 2012–2021 years with a more detailed analysis of the last six years from 2016 to 2021. A significantly high level air pollution of а near-surface ozone was revealed in the observation region, despite the absence of nearby sources of industrial emissions. The relationship of near-surface ozone concentration and meteorological parameters was investigated. Wind directions leading to increased levels of near-surface ozone pollution are established. Intra-annual variations of near-surface ozone concentration are analyzed, the factors causing the local summer minimum of surface ozone concentration in some years are established. By using the NOAA HYSPLIT model and ERA5 reanalysis, a spatial analysis of the atmospheric circulation pattern in the region was carried out. The recurrence of episodes of exceeding the ozone concentration 100 micrograms/m3 during 8 or more hours (WHO recommendation) was estimated. Possible causes of these episodes were determined. The mechanisms of long-range transport and its contribution to the near-surface ozone regime in the area of the station have been established. Annual trends of near-surface ozone concentration in the period 2012–2021 years are estimated as statistically insignificant.

A multi-perspective assessment of satellite surface Ozone products in China: Spatiotemporal variability, land cover impacts and pollution monitoring capability

A multi-perspective assessment of satellite surface Ozone products in China: Spatiotemporal variability, land cover impacts and pollution monitoring capability

Ozone stress-induced DNA methylation variations and their transgenerational inheritance in foxtail millet.

Elevated near-surface ozone (O3) concentrations have surpassed the tolerance limits of plants, significantly impacting crop growth and yield. To mitigate ozone pollution, plants must evolve a rapid and effective defense mechanism to alleviate ozone-induced damage. DNA methylation, as one of the most crucial epigenetic modifications, plays a pivotal role in maintaining gene stability, regulating gene expression, and enhancing plant resilience to environmental stressors. However, the epigenetic response of plants to O3 stress, particularly DNA methylation variations and their intergenerational transmission, remains poorly understood. This study aims to explore the epigenetic mechanisms underlying plant responses to ozone stress across generations and to identify potential epigenetic modification sites or genes crucial in response to ozone stress. Using Open Top Chambers (OTCs), we simulated ozone conditions and subjected foxtail millet to continuous ozone stress at 200 nmol mol-1 for two consecutive generations (S0 and S1). Results revealed that under high-concentration ozone stress, foxtail millet leaves exhibited symptoms ranging from yellowing and curling to desiccation, but the damage in the S1 generation was not more severe than that in the S0 generation. Methylation Sensitive Amplified Polymorphism (MSAP) analysis of the two generations indicated that ozone stress-induced methylation variations ranging from 10.82% to 13.59%, with demethylation events ranged from 0.52% to 5.58%, while hypermethylation occurred between 0.35% and 2.76%. Reproductive growth stages were more sensitive to ozone than vegetative stages. Notably, the S1 generation exhibited widespread demethylation variations, primarily at CNG sites, compared to S0 under similar stress conditions. The inheritance pattern between S0 and S1 generations was mainly of the A-A-B-A type. By recovering and sequencing methylation variant bands, we identified six stress-related differential amplification sequences, implicating these variants in various biological processes. These findings underscore the potential significance of DNA methylation variations as a critical mechanism in plants' response to ozone stress, providing theoretical insights and references for a comprehensive understanding of plant adaptation mechanisms to ozone stress and the epigenetic role of DNA methylation in abiotic stress regulation.

Large-scale ozone episodes in Europe: Decreasing sizes in the last decades but diverging changes in the future

Episodes of high near-surface ozone concentrations tend to cover large areas for several days. They are strongly dependent on meteorology, precursor emissions, and the ambient photochemical conditions. This study introduces a new pseudo-Lagrangian algorithm that identifies the spatiotemporal patterns of episodes, allowing for a good characterization of their areal extent and an assessment of their drivers. The algorithm has been used to identify ozone episodes in Europe from April to September over the last twenty years (2003-2022) in the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis as well as in the historical simulation (1950-2014) and four shared socio-economic pathways (SSPs, spanning 2015-2100) of three Earth system models (UKESM1-0-LL, EC-Earth3-AerChem and GFDL-ESM4). While the total number of episodes has increased in recent years, the frequency of large episodes has decreased following European precursor emission reductions. The analysis of the 100 largest episodes shows that they tend to occur in Northern Europe during spring and in the center and south of the continent from June onwards. Most of the top 10 episodes occurred in the first years of the century and were associated with high temperatures, enhanced solar radiation, and anticyclonic conditions. Despite the decrease in large episodes in recent years, there is uncertainty regarding future European episodes. Episodes of reduced size are found for SSPs with weak greenhouse forcing and low precursor emissions, whereas episode sizes increase in scenarios with high methane concentrations and enhanced radiative forcing, even exceeding the maximum historical size. However, the three models project episodes of different sizes for any given scenario, probably associated with their differing warming trends and the varying level of complexity in the implementation of processes. These results point to the need to implement both effective climate and air quality policies to address the ozone air pollution problem in Europe in a warming climate.

Estimation of Near-surface Ozone Concentration in the Beijing-Tianjin-Hebei Region Based on XGBoost-LME Model

High spatiotemporal resolution data on near-surface ozone concentration distribution is of great significance for monitoring and controlling atmospheric ozone pollution and improving the living environment. Using TROPOMI-L3 NO2, HCHO products, and ERA5-land high-resolution data as estimation variables, an XGBoost-LME model was constructed to estimate the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. The results showed that： ① Through correlation analysis, surface 2 m temperature （T2M）, 2 m dewpoint temperature （D2M）, surface solar radiation downwards （SSRD）, tropospheric formaldehyde （HCHO）, and tropospheric nitrogen dioxide （NO2） were important factors affecting the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. Among them, T2M, SSRD, and D2M had strong correlations, with correlation coefficients of 0.82, 0.75, and 0.71, respectively. ② Compared with that of other models, the XGBoost-LME model had the best performance in terms of various indicators. The ten-fold cross-validation evaluation indicators R2, MAE, and RMSE were 0.951, 9.27 μg·m-3, and 13.49 μg·m-3, respectively. At the same time, the model performed well at different time scales. ③ In terms of time, there was a significant seasonal difference in near-surface ozone concentration in the Beijing-Tianjin-Hebei Region in 2019, with the concentration changing in the order of summer > spring > autumn > winter. The monthly average ozone concentration in the region showed an inverted "V" trend, with a slight increase in September. The highest value occurred in July, whereas the lowest value occurred in December. In terms of spatial distribution, the near-surface ozone concentrations in the Beijing-Tianjin-Hebei Region during the months of February and March were generally at the same levels. In January, November, and December, there was a relatively insignificant trend of higher concentrations in the north and lower concentrations in the south. For the remaining months, the spatial distribution of near-surface ozone concentrations in this area predominantly exhibited a pattern of higher concentrations in the south and lower concentrations in the north. High-value areas were predominantly found in the plain regions of the southern part with lower altitudes, dense population, and higher industrial emissions； low-value areas, on the other hand, were primarily located in mountainous areas of the northern part with higher altitudes, sparse population, higher vegetation coverage, and lower industrial emissions.

WRF-Chem Modeling of Tropospheric Ozone in the Coastal Cities of the Gulf of Finland

Ozone in the troposphere is a pollutant and greenhouse gas. Atmospheric models can add valuable information to observations for studying the spatial and temporal variations in tropospheric ozone content. The present study is intended to evaluate the variability in tropospheric ozone and its precursors near the Gulf of Finland with a focus on St. Petersburg (Russia) and Helsinki (Finland) in 2016–2019, using the WRF-Chem 3-D numerical model with a spatial resolution of 10 km, together with observations. The diurnal cycle of the near-surface ozone concentrations (NSOCs) in both cities is caused by the variability in NO2 emissions, planetary boundary layer height, and local meteorological conditions. The seasonal variations in NSOCs and tropospheric ozone content (TrOC) are caused by the variability in total ozone content and in ozone formation in the troposphere. The model reveals a VOC-limited regime in the ~0–1 km layer around St. Petersburg, Helsinki, and the Gulf of Finland and a pronounced NOx-limited regime in the 0–2 km layer in the forests of southern Finland, Karelia, some Russian regions, and the Baltic countries in July. The WRF-Chem model overestimates the measured NSOCs by 10.7–43.5% and the TrOC by 7–10.4%. The observed differences are mainly caused by the errors in chemical boundary conditions and emissions of ozone precursors and by the coarse spatial resolution of the modeling.

A meta-analysis of elevated O3 effects on herbaceous plants antioxidant oxidase activity.

Increases in near-surface ozone (O3) concentrations is a global environmental problem. High-concentration O3 induces stress in plants, which can lead to visible damage to plants, reduced photosynthesis, accelerated aging, inhibited growth, and can even plant death. However, its impact has not been comprehensively evaluated because of the response differences between individual plant species, environmental O3 concentration, and duration of O3 stress in plants. We used a meta-analysis approach based on 31 studies 343 observations) to examine the effects of elevated O3 on malondialdehyde (MDA), superoxide dismutase (SOD), and peroxidase (POD) activities in herbaceous plants. Globally, important as they constitute the majority of the world's food crops. We partitioned the variation in effect size found in the meta-analysis according to the presence of plant species (ornamental herb, rice, and wheat), O3 concentration, and duration of O3 stress in plants. Our results showed that the effects of elevated O3 on plant membrane lipid peroxidation depending on plant species, O3 concentration, and duration of O3 stress in plants. The wheat SOD and POD activity was significantly lower compared to the herbs and rice (P<0.01). The SOD activity of all herbaceous plants increased by 34.6%, 10.5%, and 26.3% for exposure times to elevated O3 environments of 1-12, 13-30, and 31-60 days, respectively. When the exposure time was more than 60 days, SOD activity did not increase but significantly decreased by 12.1%. However, the POD activity of herbaceous plants increased by 30.4%, 57.3%, 21.9% and 5.81%, respectively, when exposure time of herbaceous plants in elevated O3 environment was 1-12, 13-30, 31-60 and more than 60 days. Our meta-analysis revealed that (1) rice is more resistant to elevated O3 than wheat and ornamental herbs likely because of the higher activity of antioxidant components (e.g., POD) in the symplasts, (2) exposure to elevated O3 concentrations for >60 days, may result in antioxidant SOD lose its regulatory ability, and the antioxidant component POD in the symplast is mainly used to resist O3 damage, and (3) the important factors affected the activity of SOD and POD in plants were not consistent: the duration of O3 stress in plants was more important than plant species and O3 concentration for SOD activity. However, for POD activity, plant species was the most important factor.

High-resolution estimation of near-surface ozone concentration and population exposure risk in China.

Considering the spatial and temporal effects of atmospheric pollutants, using the geographically and temporally weighted regression and geo-intelligent random forest (GTWR-GeoiRF) model and Sentinel-5P satellite remote sensing data, combined with meteorological, emission inventory, site observation, population, elevation, and other data, the high-precision ozone concentration and its spatiotemporal distribution near the ground in China from March 2020 to February 2021 were estimated. On this basis, the pollution status, near-surface ozone concentration, and population exposure risk were analyzed. The findings demonstrate that the estimation outcomes of the GTWR-GeoiRF model have high precision, and the precision of the estimation results is higher compared with that of the non-hybrid model. The downscaling method enhances estimation results to some extent while addressing the issue of limited spatial resolution in some data. China's near-surface ozone concentration distribution in space shows obvious regional and seasonal characteristics. The eastern region has the highest ozone concentrations and the lowest in the northeastern region, and the wintertime low is higher than the summertime high. There are significant differences in ozone population exposure risks, with the highest exposure risks being found in China's eastern region, with population exposure risks mostly ranging from 0.8 to 5.

Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality

The global sea surface temperatures (SSTs) are expected to change diversely in the future under different climate scenarios, which will affect the near-surface ozone (O3) distribution and concentration by influencing meteorological states and large-scale atmospheric circulation. Many countries have planned to reach carbon neutrality by the mid-21st century. In this study, the impacts of global and regional SST changes on near-surface O3 concentrations in China in the middle of the 21st century under the carbon-neutral scenario (Shared Socioeconomic Pathway 1-1.9), compared with the high-emission scenario (Shared Socioeconomic Pathway 5-8.5), and possible physical and chemical mechanisms are investigated using the Community Earth System Model version 1 (CESM1). Under future climate change, the changes in SSTs in the carbon-neutral scenario relative to the high-emission scenario lead to a dipole change in near-surface O3 concentrations in eastern and western China, with a significant decrease of 0.79 ppbv in the eastern China and a significant increase of 1.05 ppbv in the western China. The cooling of North Pacific Ocean under the carbon-neutral scenario causes a decrease in near-surface O3 concentrations by 0.48 ppbv in eastern China due to the weakened chemical production and an increase by 0.74 ppbv in western China attributed to the enhanced O3 transport from Eurasia. Cooling of Southern Hemisphere oceans leads to anomalous upward air motions over eastern China, which weaken the vertical transport of high-elevation O3 to the surface, resulting in a reduction in near-surface O3 concentrations by 0.58 ppbv in eastern China. Our results suggest that future changes in SSTs in the carbon-neutral scenario will positively benefit O3 air quality improvement in the polluted eastern China, with the North Pacific and Southern Hemisphere oceans playing important roles.

Estimation of Near-Surface Ozone Concentration Across China and Its Spatiotemporal Variations During the COVID-19 Pandemic

Estimation of Near-Surface Ozone Concentration Across China and Its Spatiotemporal Variations During the COVID-19 Pandemic

Shifting summer holidays in Spain as an adaptation measure to climate change

This paper assesses whether moving summer holidays to the warmest period of the year in Spain could be a useful climate change adaptation strategy. While the most popular period for Spanish summer holidays has traditionally been August, we illustrate that the second half of July is the hottest period of the year and when the negative effects of high temperatures are most pronounced. If the holiday period in the second fortnight of August was moved to the second fortnight of July, some of the associated impacts would be mitigated due to the reduced anthropogenic activity during non-working days. In particular, we find a significant reduction in the annual peak of labour productivity loss (~25 %) and, to a lesser extent, of electricity demand and near-surface ozone concentrations (~3-4 %). Finally, we also show that global warming could lead to enhanced differences between both fortnights (even with no change in the seasonal cycle of temperature) because of the non-linear relationships between temperature and its impacts. Therefore, the positive effect of shifting holidays would be even larger in the coming future.

Rebuilding high-quality near-surface ozone data based on the combination of WRF-Chem model with a machine learning method to better estimate its impact on crop yields in the Beijing-Tianjin-Hebei region from 2014 to 2019

In recent years, the problem of surface ozone pollution in China has been of great concern. According to observation data from monitoring stations, the concentration of near-surface ozone (O3) in China has gradually increased in recent years, and ozone concentration often exceeds the contaminant limit standard, especially in the Beijing-Tianjin-Hebei (BTH) region. High O3 concentration pollution will adversely affect crop growth, which can cause crop yield losses. Therefore, it is urgent to recognize the situation of ozone pollution in the BTH region and quantitatively evaluate the crop yield losses caused by ozone pollution to develop more effective pollution prevention and control policies. However, the monitoring of ozone concentration in China started relatively late compared with some developed countries, and currently, long-time series data covering the BTH region cannot be obtained, which makes it difficult to evaluate the impact of ozone on crop yield. Therefore, a new method (WRFC-XGB) was proposed in this study to establish a high-precision near-surface O3 concentration dataset covering the whole BTH region from 2014 to 2019 by integrating the Weather Research and Forecasting with Chemistry (WRF-Chem) model with the extreme gradient boosting (XGBoost) machine learning algorithm. Through verification with ground observation station data, the results of WRFC-XGB are satisfactory, and R2 can reach 0.78-0.91. Compared with other algorithms, the accuracy of the near-surface ozone concentration dataset is greatly improved, which can be used to estimate the impact of surface ozone on crop yield. Based on this dataset, the yield loss of winter wheat, rice, and maize caused by O3 pollution was estimated by using the response equation of the relative yield and ozone dose index. The results showed that the total yield losses of winter wheat, rice and maize from 2014 to 2019 were 2659.21 million tons, 49.23 million tons and 1721.56 million tons due to ozone pollution in the BTH region, respectively, and the highest relative yield loss of crops caused by O3 pollution could be 29.37% during 2014-2019, which indicated that the impact of ozone pollution on crop yield cannot be ignored, and effective measures need to be developed to control ozone pollution, prevent crop production loss, and ensure people's food security.

Spatiotemporal dynamics of near-surface ozone concentration and potential source areas in northern China during 2015-2020.

Near-surface ozone (O3) pollution has become one of the main factors hampering urban air quality in northern China. However, on a spatiotemporal scale, dynamic transport paths and potential source areas of O3 in northern China are ambiguous. In addition, we suspect that the contribution of transportation activities to urban O3 concentrations developed in northern China may be underestimated. In this study, the HYSPLIT, PSCF, CWT and GTWR model were used to study the transmission paths, potential source areas and driving factors of urban O3 concentration on a spatiotemporal scale. The average annual concentration of surface O3 (the 90th percentile of MDA8) was 172 ± 29μg/m3 in northern China from 2015 to 2020. In terms of inter-annual variation, the urban O3 concentration increased from 2015 to 2018, and decreased after 2018. On the spatial scale, the areas with high O3 concentration were mainly clustered in industrial cities (Tangshan, Baoding, Shijiazhuang, Xingtai and Handan). During the study period, the area with high O3 concentration in northern China shifted from northwest to southeast. From 2015 to 2020, the influence of long-distance air mass trajectories from Xinjiang and Siberi on airflow transport in Beijing city dominates (78.60%) The average percentage of short-distance transport trajectories from Shandong Peninsula region is about 21.40%. The core potential source areas of O3 pollution shifted from northwest to southeast, but the contribution to O3 pollution in Beijing gradually weakened during the same period. Temperature and relative humidity were the main meteorological driving factors affecting O3 concentration in the study area, while population density, the proportion of secondary industry in GDP, industrial smoke (dust) emissions, and passenger traffic were the main non-meteorological factors. During the period study, the influence of industrial and traffic emissions had a more significant impact on O3 concentration in northern China, which will require that more attention be paid to emission mitigation in the regional industrial and passenger transportation sector, as well as the joint prevention and control of O3 pollution in northern China in the future.

Relationship between summer time near-surface ozone concentration and planetary boundary layer height in Beijing

Relationship between summer time near-surface ozone concentration and planetary boundary layer height in Beijing

Contrasting Near-Surface Ozone Pollution in Wet and Dry Year over China.

The near-surface ozone concentration was evaluated in two typical years with contrasting climatic impacts over the China region induced by El Niño-Southern Oscillation, which had either dry conditions (drought) with intense solar radiation and higher temperatures or wet conditions with opposite meteorological conditions. Surface ozone was observed to aggravate notably by 30% over Northern China in summer and by 50% over Eastern China in autumn in the dry year compared to the wet year. The ozone aggravation was found to be mainly ascribed to the reduced precipitation (relative humidity), enhanced solar radiation and increased temperature rather than primary emission (indicated by carbon monoxide). The health impacts showed the mortality attributable to ozone sharply increased by ~55% in Guangdong while the number of cases dying from ozone-related respiratory diseases per 100,000 population at risk was elevated by ~41% and ~17% for Guangdong (in the Pearl River Delta) and Jiangsu (in the Yangtze River Delta) province (two regions that have been reported to be highly influenced by surface ozone in China), respectively, in the dry year relative to the wet year, indicative of the significant adverse health effects of ozone aggravation. These results highlight the essential contribution of climate anomalies to surface ozone pollution. Efforts to suppress ozone aggravation can be beneficial to public health if extreme drought is predicted, and reasonable policy is implemented.

基于TROPOMI的近地面臭氧浓度估算研究

基于TROPOMI的近地面臭氧浓度估算研究

Estimation of near-surface ozone concentration and analysis of main weather situation in China based on machine learning model and Himawari-8 TOAR data

Ozone (O3) is an important greenhouse gas in the atmosphere. Stratospheric ozone protects human beings, but high near-surface ozone concentrations threaten environment and human health. Owing to the uneven distribution of ground-monitoring stations and the low time resolution of polar orbiting satellites, it is difficult to accurately evaluate the refinement and synergistic pollution of near-surface ozone in China. Besides, atmospheric circulation patterns also affect ozone concentrations greatly. In this study, a new generation of geostationary satellite is used to estimate the hourly near-surface ozone concentration with a spatial resolution of 0.05°. First, the Pearson correlation coefficient and maximum information coefficient were used to study the correlation between the top of atmospheric radiation (TOAR) of Himawari-8 satellite and O3 concentration; seven TOAR channels were selected. Second, based on an interpretable deep learning model, the hourly ozone concentration in China from September 2015 to August 2021 was obtained using the TOAR-O3 model. Finally, the self-organizing map method was used to determine six major summer weather circulation patterns in China. The results showed that (1) the near-surface O3 concentration can be accurately estimated; the R2 (RMSE: μg/m3) values of the daily, monthly, and annual tenfold cross validation results were 0.91 (12.74), 0.97 (5.64), and 0.98 (1.75), respectively. The feature importance of the model showed that the temperature, TOAR, and boundary layer height contributed 38 %, 22 %, and 13 %, respectively. (2) The O3 concentration showed obvious spatiotemporal difference and gradually increased from 10:00 to 15:00 (Beijing time) every day. In most areas of China, O3 concentration had increased significantly. (3) The O3 concentration in northern China was the highest under the circulation pattern of the Meiyu front over the Yangtze River Delta, while in southern China, it was the highest under the circulation pattern of the northeast cold vortex controlling most of China.