Effects of meteorological conditions and anthropogenic precursors on ground-level ozone concentrations in Chinese cities

Observational study of ground-level ozone and climatic factors in Craiova, Romania, based on one-year high-resolution data

Air pollution is a multifaceted issue affecting people's health, environment, and biodiversity. Gaining comprehension of the interactions between natural and anthropocentric pollutant concentrations and local climate is challenging. This study aims to address the following two questions: (1) What is the influential mechanism of climatic and anthropogenic factors on the ground-level ozone (O3) concentrations in an urban environment during different seasons? (2) Can the ozone weekend effect be observed in a medium-sized city like Craiova, and under which conditions? In order to answer these questions, ozone interactions with meteorological parameters (temperature, pressure, relative humidity) and pollutant concentrations (particulate matter, carbon dioxide, volatile organic compounds, formaldehyde, nitrogen dioxide, nitric oxide and carbon monoxide) is evaluated based on a one-year dataset given by a low-cost sensor and one-year dataset provided by the National Environment Agency. Using two statistical analysis programs, Python and SPSS, a good understanding of the correlations between these variables and ozone concentration is obtained. The SPSS analysis underscores the significant impact of three meteorological factors and nine other pollutants on the ozone level. A positive correlation is noticed in the summer when sunlight is intense and photochemical reactions are elevated. The relationship between temperature and ozone concentration is strong and positive, as confirmed by Spearman's rho correlation coefficient (r = 0.880). A significant negative correlation is found between relative humidity and ozone (r = -0.590). Moreover, the analysis shows that particulate matter concentrations exhibit a significant negative correlation with ozone (r ≈ -0.542), indicating that higher particulate matter concentrations reduce ozone levels. Volatile organic compounds show a significant negative correlation with ozone (r = -0.156). A negative relationship between ozone and carbon dioxide (r = -0.343), indicates that elevated carbon dioxide levels might also suppress ozone concentrations. A significant positive correlation between nitrogen dioxide and ozone (r = 0.060), highlights the role of nitrogen dioxide in the production of ozone through photochemical reactions. However, nitric oxide shows a negative correlation with ozone (r = -0.055) due to its role in ozone formation. Carbon monoxide has no statistically significant effect on ozone concentration. To observe the differences between weekdays and weekends, T-Test was used. Even though significant differences were observed in temperature, humidity, carbon dioxide, volatile organic compounds, nitrogen dioxide, nitric oxide and carbon monoxide levels between weekdays and weekends, the T-Test did not highlight a significant weekend ozone effect in a mid-sized city as Craiova. Using Python, the daily values were calculated and compared with the limit values recommended by the World Health Organization (WHO) and European Environment Agency (EEA). The WHO O3 recommended levels were exceeded for 13 times in one year. This study offers a comprehensive understanding of ozone pollution in a mid-sized city as Craiova, serving as a valuable reference for local decision-makers. It provides critical insights into the seasonal dynamics of ozone levels, emphasizing the significant role of temperature in ozone formation and the complex interactions between various pollutants and meteorological factors.

The climate change-pollution-aerobiome nexus: A 'systems thinking' mini-review

The interrelationship between climate change, pollution and the aerobiome (the microbiome of the air) is a complex ecological dynamic with profound implications for human and ecosystem health. This mini-review explores the multifaceted relationships among these factors. By synthesising existing research and integrating interdisciplinary perspectives, we examine the mechanisms driving interactions within the climate change-pollution-aerobiome nexus. We also explore synergistic and cascading effects and potential impacts on human health (including both communicable and non-communicable diseases) and that of wider ecosystems. Based on our mini-review results, climate change influences air pollution and, independently, air pollution affects the composition, diversity and activity of the aerobiome. However, we apply a 'systems thinking' approach and create a set of systems diagrams to show that climate change likely influences the aerobiome (including bacteria and fungi) via climate change-pollution interactions in complex ways. Due to the inherent complexity of these systems, we emphasise the importance of holistic and/or interdisciplinary approaches and collaborative efforts in understanding this nexus to safeguard planetary health in an era of rapid environmental change.

Assessment of ozone pollution on rice yield reduction and economic losses in Sichuan province during 2015-2020

In recent years, there has been a significant increase in surface ozone (O3) concentrations in the troposphere. Ozone pollution has significant adverse effects on ecosystems, human health, and climate change, particularly on crop growth and yield. This study utilized the observational hourly O3 data, cumulative O3 concentration over 40 ppb per h (AOT40), and the mean daytime 7-h O3 concentration (M7) to analyze the spatiotemporal distributions of relative yield losses (RYLs) and evaluate the yield reduction and economic losses of rice in Sichuan province from 2015 to 2020. The results indicated that the average O3 concentration during the growing rice season ranged from 55.4 to 69.3 μg/m3, with the highest O3 concentration observed in 2017, and the AOT40 ranged from 4.5 to 8.7 ppm h from 2015 to 2020. At the county level, the O3 concentration, AOT40, and the relative yield loss (RYL) of rice based on AOT40 exhibited clear spatiotemporal differences in Sichuan. The RYLs of AOT40 were 4.9-9.2% from 2015 to 2020. According to AOT40 and M7 metrics, the yield loss and economic losses attributed to O3 pollution amounted to 78.75-150.36 (9.74-21.54) ten thousand tons, and 2079.08-4149.89 (257.25-594.45) million Yuan, respectively. Rice yield and economic losses were relatively large in the Chengdu Plain, southern Sichuan, and northeast Sichuan. These findings will contribute to a deeper understanding of the detrimental effects of elevated surface O3 concentrations on rice crops. It is imperative to implement more stringent O3 reduction measures aimed at lowering O3 concentrations, enhancing rice quality, and safeguarding food security in Sichuan.

Exploration of the adsorption and desorption performance of volatile organic compounds by activated carbon with different shapes based on fixed-bed experiments

Activated carbon (AC) has been widely used in volatile organic compounds (VOCs) treatment of industrial exhaust gases. Rather than modifying specific pore size distributions and surface properties, altering the shape of AC offers a more feasible approach to enhance its adsorption performance. This study investigates the adsorption-desorption performance of two different shaped ACs with highly similar properties for the removal of VOCs. The clover-shaped AC (CSAC) has a 27.46% lower internal void fraction and a 39.10% higher external void fraction compared to cylindrical AC (CAC), resulting in denser packing and longer contact time with VOCs. Adsorption experiments showed the CSAC has 40% longer adsorption breakthrough (BT) times for ethanol, ethyl acetate, and n-hexane on average, and 20% higher saturation adsorption capacity per unit volume. CSAC also has higher partition coefficients, with the highest values for ethanol, ethyl acetate, and n-hexane being 0.0187, 0.0382, and 0.0527 mol kg-1·Pa-1, respectively. The desorption process for selected VOCs is non-spontaneous and endothermic. Optimal desorption conditions were identified as an inlet space velocity of 3535 h-1, a desorption temperature of 150 °C, and a pulsed inlet method. To investigate the possibility of the application of CSAC in real-world scenarios, xylene was chosen as a representative industrial VOC. Results showed CSAC has 20% higher BT time and saturation adsorption capacity for xylene compared to CAC under different bed heights. The desorption efficiency for xylene on both ACs is below 40%. With increasing xylene inlet concentration, the mass transfer zone (MTZ) height initially increases but stabilizes beyond 1704 mg m-3. At identical bed heights, the MTZ height of CSAC is 29% shorter than CAC, indicating a higher bed utilization efficiency.

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

Investigation on ozone formation mechanism and control strategy of VOCs in petrochemical region: Insights from chemical reactivity and photochemical loss

To investigate disparities in VOCs pollution characteristics, O3 generation activity, and source apportionment outcomes resulting from photooxidation, online monitoring of 106 VOCs was conducted in Jinshan District, Shanghai from April to October 2020. The observed VOCs concentrations (VOCs-obs) were 47.1 ppbv and 59.2 ppbv for clear days (CD) and O3-polluted days (OPD), respectively. The increase in daytime concentrations of alkenes is a significant factor contributing to the enhanced atmospheric photochemical activity during the OPD period, corroborated by VOCs-loss, ozone formation potential (OFP), propy-equiv concentration, and LOH. The sensitivity analysis of O3-NOx-VOCs indicated that O3 formation was in a transitional regime towards NOx-limited conditions. The results of positive matrix factorization (PMF) demonstrated that refining and petrochemicals (20.8-25.0 %), along with oil and gas evaporation (15.6-16.7 %) were the main sources of VOCs concentrations. Notably, source apportionment based on VOCs-obs underestimated the contributions from sources of reactive components. It is worth highlighting that the sunlight impact & background source was identified as the major contributor to LOH (21.6 %) and OFP (25.3 %), signifying its significant role in O3 formation. This study reiterates the importance of controlling reactive VOC components to mitigate O3 pollution and provides a scientific foundation for air quality management, with emphasis on priority species and controlling sources.

Response of fine particulate matter and ozone concentrations to meteorology and anthropogenic precursors over the "2+26" cities of northern China

Analyzing the influencing factors of fine particulate matter and ozone formation and identifying the coupling relationship between the two are the basis for implementing the synergistic pollutants control. However, the current research on the synergistic relationship between the two still needs to be further explored. Using the Geodetector model, we analyzed the effects of meteorology and emissions on fine particulate matter and ozone concentrations over the "2 + 26" cities at multiple timescales, and also explored the coupling relationship between the two pollutants. Fine particulate matter concentrations showed overall decreasing trends on inter-season and inter-annual scale from 2015 to 2021, whereas ozone concentrations showed overall increasing trends. While ozone concentrations displayed an inverted U-shaped distribution from month to month, fine particulate matter concentrations displayed a U-shaped fluctuation. On inter-annual scale, climatic factors, with planet boundary layer height as the main determinant, have higher effects for both pollutants than human precursors. In summer and autumn, sunshine duration had the most influence on fine particulate matter, while planet boundary layer height was the greatest factor in winter. Fine particulate matter is the leading impacting factor on ozone concentrations in summer, and there were positive associations between them on both annual and seasonal scale. The impact of nitrogen oxides and volatile organic compounds for both pollutants concentrations varied significantly between seasons. The two pollutants concentration were enhanced by the interactions between the various components. On inter-annual scale, interactions between the planet boundary layer height and other factors dominated the concentrations of the two pollutants, whereas in summer, interactions between fine particulate matter and other factors dominated the concentrations of ozone. The study has implications for the treatment of atmospheric pollution in China and other nations and can serve as an important reference for the creation of integrated atmospheric pollution regulation policies over the "2 + 26" cities.

Combining physical mechanisms and deep learning models for hourly surface ozone retrieval in China

As surface ozone (O3) gains increasing attention, there is an urgent need for high temporal resolution and accurate O3 monitoring. By taking advantage of the progress in artificial intelligence, deep learning models have been applied to satellite based O3 retrieval. However, the underlying physical mechanisms that influence surface O3 into model construction have rarely been considered. To overcome this issue, we considered the physical mechanisms influencing surface O3 and used them to select relevant variable features for developing a novel deep learning model. We used a wide and deep model architecture to account for linear and non-linear relationships between the variables and surface O3. Using the developed model, we performed hourly inversions of surface O3 retrieval over China from 2017 to 2019 (9:00-17:00, local time). The validation results based on sample-based (site-based) methods yielded an R2 of 0.94 (0.86) and an RMSE of 12.79 (19.13) μg/m3, indicating the accuracy of the models. The average surface O3 concentrations in China in 2017, 2018, and 2019 were 82, 78, and 87 μg/m3, respectively. There was a diurnal pattern in surface O3 in China, with levels rising significantly from 55 μg/m3 at 9:00 a.m. to 96 μg/m3 at 15:00. Between 15:00 and 16:00, the O3 concentration remained stable at 95 μg/m3 and decreased slightly thereafter (16:00-17:00). The results of this study contribute to a deeper understanding of the physical mechanisms of ozone and facilitate further studies on ozone monitoring, thereby enhancing our understanding of the spatiotemporal characteristics of ozone.

Multi-Omics analysis reveals molecular insights into the effects of acute ozone exposure on lung tissues of normal and obese male mice

Certain sub-groups, including men and obese individuals, are more susceptible to ozone (O3) exposure, but the underlying molecular mechanisms remain unclear. In this study, the male mice were divided into two dietary groups: one fed a high-fat diet (HFD), mimicking obesity conditions, and the other fed a normal diet (ND), then exposed to 0.5 ppm and 2 ppm O3 for 4 h per day over two days. The HFD mice exhibited significantly higher body weight and serum lipid biochemical indicators compared to the ND mice. Obese mice also exhibited more severe pulmonary inflammation and oxidative stress. Using a multi-omics approach including proteomics, metabolomics, and lipidomics, we observed that O3 exposure induced significant pulmonary molecular changes in both obese and normal mice, primarily arachidonic acid metabolism and lipid metabolism. Different molecular biomarker responses to acute O3 exposure were also observed between two dietary groups, with immune-related proteins impacted in obese mice and PPAR pathway-related proteins affected in normal mice. Furthermore, although not statistically significant, O3 exposure tended to aggravate HFD-induced disturbances in lung glycerophospholipid metabolism. Overall, this study provides valuable molecular insights into the responses of lung to O3 exposure and highlights the potential impact of O3 on obesity-induced metabolic changes.

Spatiotemporal characteristics of ozone and the formation sensitivity over the Fenwei Plain

High surface ozone (O₃) levels affect human and environmental health. The Fenwei Plain (FWP), one of the critical regions for China's "Blue Sky Protection Campaign", has reported severe O₃ pollution. This study investigates the spatiotemporal properties and the causes of O₃ pollution over the FWP using high-resolution data from the TROPOspheric Monitoring Instrument (TROPOMI) from 2019 to 2021. This study characterizes spatial and temporal variations in O₃ concentration by linking O₃ columns and surface monitoring using a trained deep forest machine learning model. O₃ concentrations in summer were 2-3 times higher than those found in winter due to higher temperatures and greater solar irradiation. The spatial distributions of O₃ correlate with the solar radiation showing decreased trends from the northeastern to the southwestern FWP, with the highest O₃ values in Shanxi Province and the lowest in Shaanxi Province. For urban areas, croplands and grasslands, the O₃ photochemistry in summer is NO_x-limited or in the transitional regime, while it is VOC-limited in winter and other seasons. Reducing NO_x emissions would be effective for decreasing O₃ levels in summer, while VOC reductions are necessary for winter. The annual cycle in vegetated areas included both NO_x-limited and transitional regimes, indicating the importance of NO_x controls to protect ecosystems. The O₃ response to limiting precursors shown here is of importance for optimizing control strategies and is illustrated by emission changes during the 2020 COVID-19 outbreak.

Driving Forces of Meteorology and Emission Changes on Surface Ozone in the Huaihe River Basin, China

Surface ozone (O3) pollution in China has become a serious environmental problem in recent years. In the present study, we targeted the HRB, a large region located in China's north-south border zone, to assess the driving forces of meteorology and emission changes on surface ozone. A Kolmogorov-Zurbenko (KZ) filter method was performed on the maximum daily average 8-h (MDA8) concentrations of ozone in the HRB during 2015-2020 to decompose the original time series. The findings demonstrated that the short-term (O3ST), seasonal (O3SN), and long-term components (O3LT) of MDA8 O3 variations accounted for 34.2%, 56.1%, and 2.9% of the total variance, respectively. O3SN has the greatest influence on the daily variation in MDA8 O3, followed by O3ST. In coastal cities, the influence of O3ST was enhanced. The influence of O3SN was stronger in the northwestern HRB. Air temperature is the prevailing variable that influences the photochemical formation of ozone. A clear phase lag (7-34 days) of the baseline component between MDA8 O3 and the atmospheric temperature was found in the HRB. Using multiple linear regression, the effect of temperature on ozone was removed. We estimated that the increase in ozone concentration in the HRB was mainly caused by the emission changes (79.4%), and the meteorological conditions made a small contribution (20.6%). This study suggests that reductions in volatile organic compounds (VOCs) will play an important role in further ozone pollution reduction in the HRB.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06345-1.

An assessment of aerosol optical depth over three AERONET sites in South Africa during the year 2020

It is important to notice that the world health organization (WHO) on  the 11th of March 2020,  declared COVID-19 a global pandemic and in response governments around the world introduced lockdowns that restricted human and traffic movements including South Africa. This pandemic resulted in a total lockdown from 26 March until 16 April 2020 in South Africa with expected  decrease in atmospheric aerosols. In this present study,  the aerosol optical depth (AOD) over Southern Africa based on ground-based remotely sensed data derived from three AERONET sites (Durban, Skukuza and Upington) during 2020 were used to detrermine the restriction resopnse on atmospheric aerosol pollution  The study used data from 2019, 2018 and 2017  as base years. The AERONET derived data was complemented with the HYSPLIT Model and NCEP/NCAR Reanalysis data. The study findings show that peak increase of AOD corresponds to Angstrom exponent (AE) enhancement for two sites Durban and Skukuza during winter (JJA) while the Upington site showed a different trend where peak AOD were observed in spring (SON). The study also observed the influence of long transport airmasses particularly those originating from the Atlantic and Indian ocean moreso for the Durban and Skukuza sites (summer and autumn) thus these sites received fresh marine aerosols however this was not the case for Upington which fell under the influence of short-range inland airmasses and was likely to receive anthropogenic and dust aerosols. The major results  suggest that the lockdowns did not translate into a significant decrease in AOD levels compared to previous immediate years. The results has presented restriction response of AOD over South Africa but additional analysis is required using more locations to compare results.

A review of the factors affecting the emission of the ozone chemical precursors VOCs and NOx from the soil

The soil environment is one of the main places for the generation, emission, and absorption of various atmospheric pollutants, including nitrogen oxides (NO_x) and volatile organic compounds (VOCs), which are the main chemical precursors for the formation of ground-level ozone. Ground-level ozone pollution has become a concerning environmental problem because of the harm it poses to human health and the surrounding ecological environment. However, current studies on chemical precursors of ozone mainly focus on emissions from industrial sources, forest vegetation, and urban vehicle exhaust; by contrast, few studies have examined the role of the soil environment on NO_x and VOCs emissions. In addition, the soil environment is complex and heterogeneous. Agricultural activities (fertilization) and atmospheric deposition provide nutrients for the soil environment, with a significant effect on NO_x and VOCs emissions. There is thus a need to study the environmental factors related to the release of NO_x and VOCs in the soil to enhance our understanding of emission fluxes and the types of NO_x and VOCs in the soil environment and aid efforts to control ground-level ozone pollution through appropriate measures such as management of agricultural activities. This paper reviews the generation of NO_x and VOCs in the soil environment and the effects of various environmental factors on this process. Some suggestions are provided for future research on the regulation of NO_x and VOCs emissions in the soil environment and the ability of the soil environment to contribute to ground-level ozone pollution.

Maize yield reduction and economic losses caused by ground-level ozone pollution with exposure- and flux-response relationships in the North China Plain

Ground-level ozone (O₃) has negative effects on agricultural crops. Maize is an important grain crop in China. The North China Plain (NCP) serves as the major crops' production area of China and experiences severe ozone pollution. Using the ground-level ozone simulated by an atmospheric chemistry transport model (WRF-Chem), we quantified the yield reduction and economic losses of maize during 2015-2018 over NCP based on exposure-response AOT40 (accumulation of hourly O₃ concentration exceed 40 ppb) and flux-response POD₆ (phytotoxic dose of ozone over 6 nmol m^-2 s^-1). Results showed that the ozone concentration, AOT40, and POD₆ clearly increased from 2015 to 2018 in growing season of maize over NCP. The four-year annual mean ozone concentration, AOT40, and POD₆ were 0.055 ppm, 18.02 ppm h, and 5.02 mmol m^-2, respectively. At county level, the relative loss of maize yield (MRYL) based on AOT40 and POD₆ had clearly spatio-temporal differences in NCP. The average MRYLs of AOT40 and of POD₆ from 2015 to 2018 were 10.4% and 21.4%, respectively, and these reductions were associated with 2399 million and 5637 million US dollars, respectively. This study suggests that surface ozone increased the yield losses of maize, and indicates that further reductions in ozone concentrations can enhance the food security in China.

Staggered-peak production is a mixed blessing in the control of particulate matter pollution

Staggered-peak production (SP)-a measure to halt industrial production in the heating season-has been implemented in North China Plain to alleviate air pollution. We compared the variations of PM1 composition in Beijing during the SP period in the 2016 heating season (SPhs) with those in the normal production (NP) periods during the 2015 heating season (NPhs) and 2016 non-heating season (NPnhs) to investigate the effectiveness of SP. The PM1 mass concentration decreased from 70.0 ± 54.4 μg m-3 in NPhs to 53.0 ± 56.4 μg m-3 in SPhs, with prominent reductions in primary emissions. However, the fraction of nitrate during SPhs (20.2%) was roughly twice that during NPhs (12.7%) despite a large decrease of NOx, suggesting an efficient transformation of NOx to nitrate during the SP period. This is consistent with the increase of oxygenated organic aerosol (OOA), which almost doubled from NPhs (22.5%) to SPhs (43.0%) in the total organic aerosol (OA) fraction, highlighting efficient secondary formation during SP. The PM1 loading was similar between SPhs (53.0 ± 56.4 μg m-3) and NPnhs (50.7 ± 49.4 μg m-3), indicating a smaller difference in PM pollution between heating and non-heating seasons after the implementation of the SP measure. In addition, a machine learning technique was used to decouple the impact of meteorology on air pollutants. The deweathered results were comparable with the observed results, indicating that meteorological conditions did not have a large impact on the comparison results. Our study indicates that the SP policy is effective in reducing primary emissions but promotes the formation of secondary species.

Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign

Surface ozone (O₃), one of the harmful air pollutants, generated significantly negative effects on human health and plants. Existing O₃ datasets with coarse spatiotemporal resolution and limited coverage, and the uncertainties of O₃ influential factors seriously restrain related epidemiology and air pollution studies. To tackle above issues, we proposed a novel scheme to estimate daily O₃ concentrations on a fine grid scale (1 km × 1 km) from 2018 to 2020 across China based on machine learning methods using hourly observed ground-level pollutant concentrations data, meteorological data, satellite data, and auxiliary data including digital elevation model (DEM), land use data (LUD), normalized difference vegetation index (NDVI), population (POP), and nighttime light images (NTL), and to identify the difference of influential factors of O₃ on diverse urbanization and topography conditions. Some findings were achieved. The correlation coefficients (R²) between O₃ concentrations and surface net solar radiation (SNSR), boundary layer height (BLH), 2 m temperature (T2M), 10 m v-component (MVW), and NDVI were 0.80, 0.40, 0.35, 0.30, and 0.20, respectively. The random forest (RF) demonstrated the highest validation R² (0.86) and lowest validation RMSE (13.74 μg/m³) in estimating O₃ concentrations, followed by support vector machine (SVM) (R² = 0.75, RMSE = 18.39 μg/m³), backpropagation neural network (BP) (R² = 0.74, RMSE = 19.26 μg/m³), and multiple linear regression (MLR) (R² = 0.52, RMSE = 25.99 μg/m³). Our China High-Resolution O₃ Dataset (CHROD) exhibited an acceptable accuracy at different spatial-temporal scales. Additionally, O₃ concentrations showed decreasing trend and represented obviously spatiotemporal heterogeneity across China from 2018 to 2020. Overall, O₃ was mainly affected by human activities in higher urbanization regions, while O₃ was mainly controlled by meteorological factors, vegetation coverage, and elevation in lower urbanization regions. The scheme of this study is useful and valuable in understanding the mechanism of O₃ formation and improving the quality of the O₃ dataset.

Effects of Seasonal Variation on Spatial and Temporal Distributions of Ozone in Northeast China

The levels of tropospheric ozone (O₃) are closely related to regional meteorological conditions, precursor emissions, and geographical environments, which have a significant negative impact on human health. The concentrations of O₃ were relatively low, while the spatial distribution was strongly heterogeneous in Northeast China; however, little is known about how the influencing factors affect the distribution of O₃ in Northeast China. Here, the O₃ concentration, meteorological observation data, precursors (NO₂), and vegetation coverage data from 41 monitoring cities in Northeast China from 2017 to 2020 were collected and analyzed. The spatial-temporal distributions and evolution characteristics of O₃ concentrations were investigated using statistical analysis, kriging interpolation, spatial autocorrelation analysis, cold-hot spot analysis, and geographic detectors, and the effects of meteorological factors, NO₂, and green land area on O₃ concentrations were evaluated seasonally and spatially. The results showed that O₃ pollution in Northeast China was generally at a relatively low level and showed a decreasing trend during 2017-2020, with the highest concentrations in the spring and the lowest concentrations in the autumn and winter. May-July had relatively high O₃ concentrations, and the over-standard rates were also the highest (>10%). The spatial distribution showed that the O₃ concentration was relatively high in the south and low in the northeast across the study area. A globally significant positive correlation was derived from the spatial autocorrelation analysis. The cold-hot spot analysis showed that O₃ concentrations exhibited spatial agglomerations of hot spots in the south and cold spots in the north. In Northeast China, the south had hot spots with high O₃ pollution, the north had cold spots with excellent O₃ levels, and the central region did not exhibit strong spatial agglomerations. A weak significant negative correlation between O₃ and NO₂ indicated that the emissions of NOx derived from human activities have weak effects on the O₃ concentrations, and wind speed and sunshine duration had little effect on spatial differentiation of the O₃ concentrations. Spatial variability in O₃ concentrations in the spring and autumn was mainly driven by temperature, but in the summer, the influence of temperature was weakened by the relative humidity and precipitation; no factor had strong explanatory power in the winter. The temperature was the only controlling factor in hot spots with high O₃ concentrations. In cold spots with low O₃ concentrations, the relative humidity and green land area jointly affected the spatial distributions of O₃.

Ozone pollution in the plate and logistics capital of China: Insight into the formation, source apportionment, and regional transport

As the logistics and plate capital of China, the sources and regional transport of O₃ in Linyi are different from those in other cities because of the significant differences in industrial structure and geographical location. Twenty-five ozone pollution episodes (OPEs, 52 days) were identified in 2021, with a daily maximum 8-h moving average O₃ concentration (O_3-MDA8) of 184.5 ± 22.5 μg/m³. Oxygenated volatile organic compounds (OVOCs) and aromatics were the dominant contributors to ozone formation potential (OFP), with contributions of approximately 23.5-52.7% and 20.0-40.8%, respectively, followed by alkenes, alkanes, and alkynes. Formaldehyde, an OVOC with high concentrations emitted from the plate industry and vehicles, contributed the most to OFP (22.7 ± 5.5%), although formaldehyde concentrations only accounted for 9.4 ± 2.7% of the total non-methane hydrocarbon (NMHC) concentrations. The source apportionment results indicated that the plate industry was the dominant O₃ contributor (27.0%), followed by other sources (21.6%), vehicle-related sources (18.0%), solvent use (16.9%), liquefied petroleum gas (LPG)/natural gas (NG) (8.8%), and combustion sources (7.7%). Therefore, there is an urgent need to control the plating industry in Linyi to mitigate O₃ pollution. The backward trajectory, potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models were used to identify the air mass pathways and potential source areas of air pollutants during the OPEs. O₃ pollution was predominantly affected by air masses that originated from eastern and local regions, while trajectories from the south contained the highest O₃ concentrations (207.0 μg/m³). The potential source area was from east and south Linyi during the OPEs. Therefore, it is critical to implement regional joint prevention and control measures to lower O₃ concentrations.

Observed sensitivities of PM2.5 and O3 extremes to meteorological conditions in China and implications for the future

Frequent extreme air pollution episodes in China accompanied with high concentrations of particulate matters (PM2.5) and ozone (O3) are partly supported by meteorological conditions. However, the relationships between meteorological variables and pollution extremes can be poorly estimated solely based on mean pollutant level. In this study, we use quantile regression to investigate meteorological sensitivities of PM2.5 and O3 extremes, benefiting from nationwide observations of air pollutants over 2013-2019 in China. Results show that surface winds and humidity are identified as key drivers for high PM2.5 events during both summer and winter, with greater sensitivities at higher percentiles. Higher humidity favors the hydroscopic growth of particles during winter, but it tends to decrease PM2.5 through wet scavenging during summer. Surface temperature play dominant role in summer O3 extremes, especially in VOC-limited regime, followed by surface winds and radiation. Sensitivities of O3 to meteorological conditions are relatively unchanging across percentiles. Under the fossil-fueled development pathway (SSP5-8.5) scenario, meteorological conditions are projected to favor winter PM2.5 extremes in North China Plain (NCP), Yangtze River Delta (YRD) and Sichuan Basin (SCB), mainly due to enhanced surface specific humidity. Summer O3 extremes are likely to occur more frequently in the NCP and YRD, associated with warmer temperature and stronger solar radiation. Besides, meteorological conditions over a relatively longer period play a more important role in the formation of pollution extremes. These results improve our understanding of the relationships between extreme PM2.5 and O3 pollution and meteorology, and can be used as a valuable reference of model predicted air pollution extremes.

Contribution of local and surrounding area anthropogenic emissions to a high ozone episode in Zhengzhou, China

This study analyzed an ozone pollution episode that occurred in the summer of 2020 in Zhengzhou, the provincial capital of Henan, China, and quantified the contribution of local and surrounding area anthropogenic emissions to this episode based on the Weather Research and Forecasting with Chemistry (WRF/Chem) model. Simulation results showed that the WRF/Chem model is well suited to simulate the ozone concentrations in this area. In addition, four simulation scenarios (removing the emissions from the northern Zhengzhou, southwestern Zhengzhou, Zhengzhou local and southeastern Zhengzhou) were conducted to explore the specific contributions of local emissions and emissions from surrounding areas within Henan to this ozone pollution episode. We found that contributions from the northern, local, southwestern, and southeastern regions were 6.1%, 5.9%, 1.7%, and 1.5%, respectively. The northern and local emissions of Zhengzhou (only emissions from Zhengzhou) were prominent contributors within the simulation areas. In other words, during this episode, most of the ozone pollution in Zhengzhou appeared to be transported in from regions outside Henan Province.

Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China

Variations in marine and terrestrial geographical environments can cause considerable differences in meteorological conditions, economic features, and population density (PD) levels between coastal and inland cities, which in turn can affect the urban air quality. In this study, a five-year (2016-2020) dataset encompassing air monitoring (from the China National Environmental Monitoring Centre), socioeconomic statistical (from the Shandong Province Bureau of Statistics) and meteorological data (from the U.S. National Centers for Environmental Information, National Oceanic and Atmospheric Administration) was employed to investigate the spatiotemporal distribution characteristics and underlying drivers of urban ozone (O₃) in Shandong Province, a region with both land and sea environments in eastern China. The main research methods included the multiscale geographically weighted regression (MGWR) model and wavelet analysis. From 2016 to 2019, the O₃ concentration increased year by year in most cities, but in 2020, the O₃ concentration in all cities decreased. O₃ concentration exhibited obvious regional differences, with higher levels in inland areas and lower levels in eastern coastal areas. The MGWR analysis results indicated the relationship between PD, urbanization rate (UR), and O₃ was greater in coastal cities than that in the inland cities. Furthermore, the wavelet coherence (WTC) analysis results indicated that the daily maximum temperature was the most important factor influencing the O₃ concentration. Compared with NO, NO₂, and NO_x (NO_x ≡ NO + NO₂), the ratio of NO₂/NO was more coherent with O₃. In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM_2.5) exerted a greater impact on O₃ in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O₃ differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O₃ pollution control in coastal and inland cities.

Hourly Seamless Surface O3 Estimates by Integrating the Chemical Transport and Machine Learning Models in the Beijing-Tianjin-Hebei Region

Surface ozone (O3) is an important atmospheric trace gas, posing an enormous threat to ecological security and human health. Currently, the core objective of air pollution control in China is to realize the joint treatment of fine particulate matter (PM2.5) and O3. However, high-accuracy near-surface O3 maps remain lacking. Therefore, we established a new model to determine the full-coverage hourly O3 concentration with the WRF-Chem and random forest (RF) models combined with anthropogenic emission data and meteorological datasets. Based on this method, choosing the Beijing-Tianjin-Hebei (BTH) region in 2018 as an example, full-coverage hourly O3 maps were generated at a horizontal resolution of 9 km. The performance evaluation results indicated that the new model is reliable with a sample (station)-based 10-fold cross-validation (10-CV) R2 value of 0.94 (0.90) and root mean square error (RMSE) of 14.58 (19.18) µg m−3. In addition, the estimated O3 concentration is accurately determined at varying temporal scales with sample-based 10-CV R2 values of 0.96, 0.98 and 0.98 at the daily, monthly, and seasonal scales, respectively, which is highly superior to traditional derivation algorithms and other techniques in previous studies. An initial increase and subsequent decrease, which constitute the diurnal variation in the O3 concentration associated with temperature and solar radiation variations, were captured. The highest concentration reached approximately 112.73 ± 9.65 μg m−3 at 15:00 local time (1500 LT) in the BTH region. Summertime O3 posed a high pollution risk across the whole BTH region, especially in southern cities, and the pollution duration accounted for more than 50% of the summer season. Additionally, 43 and two days exhibited light and moderate O3 pollution, respectively, across the BTH region in 2018. Overall, the new method can be beneficial for near-surface O3 estimation with a high spatiotemporal resolution, which can be valuable for research in related fields.

Spatiotemporal Dynamics of Surface Ozone and Its Relationship with Meteorological Factors over the Beijing-Tianjin-Tangshan Region, China, from 2016 to 2019

In recent years, ozone pollution has been increasing in some parts of the world. In this study, we used the Beijing-Tianjin-Tangshan (BJ-TJ-TS) urban agglomeration region as a case study and used satellite remotely sensed inversion data and hourly ground monitoring observations of surface ozone concentrations, meteorological data, and other factors from 2016 to 2019 to explore the spatiotemporal dynamic characteristics of surface ozone concentration and its pollution levels. We also investigated their coupling relationships with meteorological factors, including temperature, pressure, relative humidity, wind velocity, and sunshine duration, in order to support the development of effective control measures for regional ozone pollution. The results revealed that the surface ozone concentration throughout the BJ-TJ-TS region from 2016 to 2019 exhibited an overall pattern of high values in the northwest and low values in the southeast, as well as an obvious difference between built-up and non-built-up areas (especially in Beijing). Meanwhile, a notable increasing trend of ozone levels was discovered in the BJ and TJ areas from 2016 to 2019, whereas this upward trend was not evident in the TS area. In all three areas, the highest monthly average ozone values occurred in the summer month of June, while the lowest monthly average levels occurred in the winter month of December. Their diurnal variation values reached a maximum value at approximately 3:00-4:00 p.m. and a minimum value at approximately 7:00 a.m. It is clear that high temperature, long sunshine duration, low atmospheric pressure, and weak wind velocity conditions, as well as certain relative humidity levels, readily led to high-concentration ozone pollution. Meanwhile, the daily average values of the five meteorological factors on days with Grade I and Grade II ozone pollution displayed different characteristics.

Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)

With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O3 with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index Gi* were adopted to reveal the spatial agglomeration of O3 pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m−3 increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O3 concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O3 concentration reached 200 μg·m−3 in North China (NC) in June, while the lowest value was 60 μg·m−3 in Northeast China (NEC) in December. O3 is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O3 concentrations are significantly differentiated in space: O3 pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O3 exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.

Clustering Analysis on Drivers of O3 Diurnal Pattern and Interactions with Nighttime NO3 and HONO

The long-path differential optical absorption spectroscopy (LP-DOAS) technique was deployed in Shanghai to continuously monitor ozone (O3), formaldehyde (HCHO), nitrogen dioxide (NO2), nitrous acid (HONO), and nitrate radical (NO3) mixing ratios from September 2019 to August 2020. Through a clustering method, four typical clusters of the O3 diurnal pattern were identified: high during both the daytime and nighttime (cluster 1), high during the nighttime but low during the daytime (cluster 2), low during both the daytime and nighttime (cluster 3), and low during the nighttime but high during the daytime (cluster 4). The drivers of O3 variation for the four clusters were investigated for the day- and nighttime. Ambient NO caused the O3 gap after midnight between clusters 1 and 2 and clusters 3 and 4. During the daytime, vigorous O3 generation (clusters 1 and 4) was found to accompany higher temperature, lower humidity, lower wind speed, and higher radiation. Moreover, O3 concentration correlated with HCHO for all clusters except for the low O3 cluster 3, while O3 correlated with HCHO/NOx, but anti-correlated with NOx for all clusters. The lower boundary layer height before midnight hindered O3 diffusion and accordingly determined the final O3 accumulation over the daily cycle for clusters 1 and 4. The interactions between the O3 diel profile and other atmospheric reactive components established that higher HONO before sunrise significantly promoted daytime O3 generation, while higher daytime O3 led to a higher nighttime NO3 level. This paper summarizes the interplays between day- and nighttime oxidants and oxidation products, particularly the cause and effect for daytime O3 generation from the perspective of nighttime atmospheric components.

A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology

Estimating ground-level ozone concentrations is crucial to study the adverse health effects of ozone exposure and better understand the impacts of ground-level ozone on biodiversity and vegetation. However, few studies have attempted to use satellite retrieved ozone as an indicator given their low sensitivity in the boundary layer. Using the Troposphere Monitoring Instrument (TROPOMI)'s total ozone column together with the ozone profile information retrieved by the Ozone Monitoring Instrument (OMI), as TROPOMI ozone profile product has not been released, we developed a machine learning model to estimate daily maximum 8-hour average ground-level ozone concentration at 10 km spatial resolution in California. In addition to satellite parameters, we included meteorological fields from the High-Resolution Rapid Refresh (HRRR) system at 3 km resolution and land-use information as predictors. Our model achieved an overall 10-fold cross-validation (CV) R² of 0.84 with root mean square error (RMSE) of 0.0059 ppm, indicating a good agreement between model predictions and observations. Model predictions showed that the suburb of Los Angeles Metropolitan area had the highest ozone levels, while the Bay Area and the Pacific coast had the lowest. High ozone levels are also seen in Southern California and along the east side of the Central Valley. TROPOMI data improved the estimate of extreme values when compared to a similar model without it. Our study demonstrates the feasibility and value of using TROPOMI data in the spatiotemporal characterization of ground-level ozone concentration.

The effect of water stress on net primary productivity in northwest China

Net primary productivity (NPP) has been widely used as the indicator of vegetation function and exhibits large spatial and temporal variations caused by numerous factors. Northwest China (NWC) is one of the driest regions in China, and water supply is the key determinant of NPP here. However, studies on the effects of water stress on NPP in NWC at the regional scale are still relatively lacking. Thus, in this study, based on a set of Moderate-Resolution Imaging Spectroradiometer (MODIS) NPP and evapotranspiration (ET) datasets, we quantified the response of NPP to water stress, which is indicated by crop water stress index (CWSI). Regional average of annual NPP in NWC showed an increasing trend during the study period, at a rate of 0.84 g C m-2 yr-1. At the province level, the NPP increase rates increased in the order of Ningxia (7.7%), Shaanxi (6.5%), Gansu (4.5%), Qinghai (3.8%), and Xinjiang (1.7%). NPP was negatively correlated with CWSI (p<0.05) in 73% of areas, indicating the key role of water stress in constraining NPP over this arid region. The effect of water stress on NPP changes with elevation. Water stress has the strongest negative impact on NPP in areas with elevations around 2000 m. In elevations above 5000 m, NPP is not limited by water stress, mostly positively correlated with CWSI. Our findings further clarify the importance of water stress in dryland ecosystems, while highlighting that elevation gradients can significantly affect the correlation between NPP and water stress.

Removing the effects of meteorological factors on changes in nitrogen dioxide and ozone concentrations in China from 2013 to 2020

Previous studies on long-term ozone (O₃) variations in China have reported inconsistent conclusions on the role of meteorological factors in controlling said variations. In this study, we used an observation-based decomposition model to conduct an up-to-date investigation of the effects of meteorological factors on the variations in nitrogen dioxide (NO₂) and O₃ concentrations in China in the summer from 2013 to 2020. The variations in NO₂ and O₃ concentrations after removing the major meteorological effects were then analyzed to improve our understanding of O₃ formation regimes. Ground measurements show that both NO₂ and O₃ concentrations decreased in eastern, central, and southeastern China (e.g., NO₂ and O₃ concentrations in Wuhan reduced by 4.3 and 6.2 ppb, respectively), which was not anticipated. Analyses of meteorological effects showed that reduced wind strength, decreased temperature, and increased relative humidity significantly reduced O₃ concentrations in eastern and central China (e.g., by 10.5 ppb in Wuhan). After removing the major meteorological effects, the O₃ trends were reversed in eastern and central China (e.g., increased by 4.9 ppb in Wuhan). The contrasting trends in NO₂ and O₃ concentrations suggest that their O₃ formations were sensitive to volatile organic compounds (VOC-limited regime). In southeastern China, both NO₂ and O₃ concentrations decreased, implying that the O₃ formation regimes changed to mixed sensitive or nitrogen oxide-limited (NO_x-limited) regimes. The meteorological effects varied by region and may play a dominant role in controlling the long-term O₃ variation. Our results indicate that the attribution of O₃ variation to emission control without accounting for meteorological effects can be misleading.

Spatio-Temporal Evolution and Spatial Heterogeneity of Influencing Factors of SO2 Emissions in Chinese Cities: Fresh Evidence from MGWR

In this study, based on the multi-source nature and humanities data of 270 Chinese cities from 2007 to2018, the spatio-temporal evolution characteristics of SO2 emissions are revealed by using Moran’s I, a hot spot analysis, kernel density, and standard deviation ellipse models. The spatial scale heterogeneity of influencing factors is explored by using the multiscale geographically weighted regression model to make the regression results more accurate and reliable. The results show that (1) SO2 emissions showed spatial clustering characteristics during the study period, decreased by 85.12% through pollution governance, and exhibited spatial heterogeneity of differentiation. (2) The spatial distribution direction of SO2 emissions’ standard deviation ellipse in cities was “northeast–southwest”. The gravity center of the SO2 emissions shifted to the northeast, from Zhumadian City to Zhoukou City in Henan Province. The results of hot spots showed a polarization trend of “clustering hot spots in the north and dispersing cold spots in the south”. (3) The MGWR model is more accurate than the OLS and classical GWR regressions. The different spatial bandwidths have a different effect on the identification of influencing factors. There were several main influencing factors on urban SO2 emissions: the regional innovation and entrepreneurship level, government intervention, and urban precipitation; important factors: population intensity, financial development, and foreign direct investment; secondary factors: industrial structure upgrading and road construction. Based on the above conclusions, this paper explores the spatial heterogeneity of urban SO2 emissions and their influencing factors, and provides empirical evidence and reference for the precise management of SO2 emission reduction in “one city, one policy”.

Effects of Anthropogenic Emissions from Different Sectors on PM2.5 Concentrations in Chinese Cities

PM_2.5 pollution has gradually attracted people's attention due to its important negative impact on public health in recent years. The influence of anthropogenic emission factors on PM_2.5 concentrations is more complicated, but their relative individual impact on different emission sectors remains unclear. With the aid of the geographic detector model (GeoDetector), this study evaluated the impacts of anthropogenic emissions from different sectors on the PM_2.5 concentrations of major cities in China. The results indicated that the influence of anthropogenic emissions factors with different emission sectors on PM_2.5 concentrations exhibited significant changes at different spatial and temporal scales. Residential emissions were the dominant driver at the national annual scale, and the NO_X of residential emissions explained 20% (q = 0.2) of the PM_2.5 concentrations. In addition, residential emissions played the leading role at the regional annual scale and during most of the seasons in northern China, and ammonia emissions from residents were the dominant factor. Traffic emissions play a leading role in the four seasons for MUYR and EC in southern China, MYR and NC in northern China, and on a national scale. Compared with primary particulate matter, secondary anthropogenic precursors have a more important effect on PM_2.5 concentrations at the national or regional annual scale. The results can help to strengthen our understanding of PM_2.5 pollution, improve PM_2.5 forecasting models, and formulate more precise government control policy.

The diurnal cycle of summer tropospheric ozone concentrations across Chinese cities: Spatial patterns and main drivers

China is experiencing severe tropospheric ozone pollution, especially during the summer period in cities. Previous studies have assessed the role of meteorological conditions and anthropogenic precursors in shaping the diurnal variation of ozone concentration in some Chinese cities or the spatial patterns of daytime ozone concentration, but less is known about the spatial variation and main regulators of the diurnal cycle of summer ozone concentrations in Chinese cities. Using monitoring data from 367 cities, we analyzed the spatial patterns and main regulators of daytime maximum, nighttime minimum and diurnal difference of summer (June-August) ozone concentration during 2015-2019. National mean values and standard deviations of daytime maximum and nighttime minimum of summer surface ozone concentration were 124.1 ± 27.5 and 33.4 ± 13.0 μg m^-3, resulting in a diurnal difference of 90.7 ± 25.2 μg m^-3. High values of daytime maximum, nighttime minimum, and diurnal difference of summer ozone concentration occurred in cities in northern China, especially in the North China Plain, and several city agglomerations in southern China. Daytime maximum ozone concentration was higher in cities with higher daytime PM_2.5 and NO₂ concentrations, lower daytime precipitation and lower elevation. Nighttime minimum ozone concentration increased with lower nighttime precipitation, lower NO₂ concentration and CO concentration, higher nighttime maximum PM_2.5 concentration and higher elevation. Diurnal difference of ozone concentration increased with lower elevation, lower daytime precipitation, and higher diurnal difference of CO and NO₂ concentrations. Our findings highlight different regulators for daytime and nighttime ozone and imply the need of joint regulation of PM_2.5 and NO₂ emissions to control ozone pollution.

Spatiotemporal variations of ambient air pollutants and meteorological influences over typical urban agglomerations in China during the COVID-19 lockdown

To investigate the air quality change during the COVID-19 pandemic, we analyzed spatiotemporal variations of six criteria pollutants in nine typical urban agglomerations in China using ground-based data and examined meteorological influences through correlation analysis and backward trajectory analysis under different responses. Concentrations of PM_2.5, PM₁₀, NO₂, SO₂ and CO in urban agglomerations respectively decreased by 18%-45% (30%-62%), 17%-53% (22%-39%), 47%-64% (14%-41%), 9%-34% (0%-53%) and 16%-52% (23%-56%) during Lockdown (Post-lockdown) period relative to Pre-lockdown period. PM_2.5 pollution events occurred during Lockdown in Beijing-Tianjin-Hebe (BTH) and Middle and South Liaoning (MSL), and daily O₃ concentration rose to grade Ⅱ standard in Post-lockdown period. Distinct from the nationwide slump of NO₂ during Lockdown period, a rebound (∼40%) in Post-lockdown period was observed in Cheng-Yu (CY), Yangtze River Middle-Reach (YRMR), Yangtze River Delta (YRD) and Pearl River Delta (PRD). With slightly higher wind speed compared with 2019, the reduction of PM_2.5 (51%-62%) in Post-lockdown period is more than 2019 (15%-46%) in HC (Harbin-Changchun), MSL, BTH, CP (Central Plain) and SP (Shandong-Peninsula), suggesting lockdown measures are effective to PM_2.5 alleviation. Although O₃ concentrations generally increased during the lockdown, its increment rate declined compared with 2019 under similar sunlight duration and temperature. Additionally, unlike HC, MSL and BTH, which suffered from additional (> 30%) air masses from surrounding areas after the lockdown, the polluted air masses reaching YRD and PRD mostly originated from the long-distance transport, highlighting the importance of joint regional governance.

Responses of decline in air pollution and recovery associated with COVID-19 lockdown in the Pearl River Delta

The Guangdong government implemented lockdown measures on January 23, 2020, to ease the spread of the coronavirus disease 2019 (COVID-19). These measures prohibit a series of human activities and lead to a great reduction in anthropogenic emissions. Starting on February 20, all companies resumed work and production, and emissions gradually recovered. To investigate the response of air pollutants in the Pearl River Delta (PRD) to the emission reduction and recovery related to COVID-19 lockdown, we used the Community Multi-scale Air Quality (CMAQ) model to estimate the changes in air pollutants, including three periods: Period I (January 10 to January 22, 2020), Period II (January 23 to February 19, 2020), Period III (February 20 to March 9, 2020). During Period II, under the concurrent influence of emissions and meteorology, air quality improved significantly with PM2.5, NO2, and SO2 decreased by 52%, 67%, and 25%, respectively. O3 had no obvious changes in most cities, which mainly due to the synergetic effects of emissions and meteorology. In Period III, with the recovery of emissions and the changes in meteorology, the increase of secondary components was faster than that of primary PM2.5 (PPM), which indicated that changes in PPM concentration were more sensitive to emissions reduction. O3 concentration increased as emission and temperature rising. Our findings elucidate that more effective emission control strategies should be implemented in PRD to alleviate the increasingly serious pollution situation.

Ozone Concentration Levels in Urban Environments-Upper Silesia Region Case Study

Although ozone (O3) plays a crucial role in screening the Earth's surface and lower atmosphere layers from the ultraviolet radiation, troposphere ozone is proven to have negative health effects on the human body and is one of the greenhouse gases. The objective of this study was to perform a measurement-based assessment for determining whether the concentration of ozone is within admissible limits, or exceeded, in Silesia Province and does not pose a threat to the local population. The data provided by the Voivodship Inspectorate for Environmental Protection in Katowice were used in the analysis. The received data constitute the result of 8-h measurements of concentrations of ozone at selected air monitoring stations of the Silesian province. The locations of three monitoring stations were found to be useful for the aim of this research; one site is situated in a rural background area; another one is located in a medium-sized city and the Katowice station is representative for an urban background situation. We used cluster analysis, weighted pair group method using arithmetic averages (WPGMA) and Chebyshev distances to test the hypothesis and compare empirical distributions in the general population. The alarm level has not been exceeded in indicated measurements stations in Silesian Voivodship in the period 2015-2017 (averaging time 1 h: 240 µg/m3 for 3 h). The target level was exceeded in 2015 at all three measurements stations and in the following years at one station (in Zloty Potok, 2016, and in Katowice, 2017). Each year, the largest number of exceedances occurred in August. The results clearly indicate a lack of hazards for the general population's health in terms of increased concentrations of ozone in the city centers and outside. The results confirm that environmental conditions (i.e., landform, the area surrounding monitoring station) have a significant influence on the ozone level.

Multi-scale volatile organic compound (VOC) source apportionment in Tianjin, China, using a receptor model coupled with 1-hr resolution data

The multi-scale chemical characteristics and source apportionment of volatile organic compounds (VOCs) were analysed in Tianjin, China, using 1-hr resolution VOC-species data between November 1, 2018 and March 15, 2019. The average total VOC (TVOC) concentration was 30.6 ppbv during the heating season. The alkanes accounted for highest proportion of the TVOC, while the alkenes were the predominant species forming ozone, especially ethylene. Compared to the clean period, the concentration of acetylene during the haze events showed highest increase rate, followed by the ethane; and the concentrations and proportions of alkanes and alkenes were highest during the growth stage (GS) of haze events. The multi-scale apportionment results suggested petrochemical industry and solvent usage (PI/SU, 31.2%), vehicle emissions and liquefied petroleum gas (VE/LPG, 20.5%), and combustion emissions (CE, 19.1%) were the main VOC sources during the heating season. Compared to the clean period, the contributions of PI/SU, VE/LPG, CE, and refinery emissions notably increased during the haze events, while that of gasoline evaporation decreased. The contributions of PI/SU and RPI showed significantly increase during the GS of haze events, whereas most sources decreased during the dissipation stage of haze events. Diurnal-variations in source contributions during the haze events were clearer than the clean period, and the contributions of PI/SU, VE/LPG, and CE during the haze events were markedly higher at night. These findings provide valuable information to inform effective VOC control and prevention measures with specific relevance for the control of ozone pollution in Tianjin.