Satellite-Based Long-Term Spatiotemporal Patterns of Surface Ozone Concentrations in China: 2005-2019

Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning

Accurately mapping ground-level ozone concentrations at high spatiotemporal resolution (daily, 1 km) is essential for evaluating human exposure and conducting public health assessments. This requires identifying and understanding a proxy that is well-correlated with ground-level ozone variation and available with spatiotemporal high-resolution data. This study introduces a high-resolution ozone modeling method utilizing the XGBoost algorithm with satellite-derived land surface temperature (LST) as the primary predictor. Focusing on China in 2019, our model achieved a cross-validation R2 of 0.91 and a root-mean-square error (RMSE) of 13.51 μg/m3. We provide detailed maps highlighting ground-level ozone concentrations in urban areas, uncovering spatial variations previously unresolved, along with time series aligning with established understandings of ozone dynamics. Our local interpretation of the machine learning model underscores the significant contribution of LST to spatiotemporal ozone variations, surpassing other meteorological, pollutant, and geographical predictors in its influence. Validation results indicate that model performance decreases as spatial resolution becomes coarser, with R2 decreasing from 0.91 for the 1 km model to 0.85 for the 25 km model. The methodology and data sets generated by this study offer new insights into ground-level ozone variability and mapping and can significantly aid in exposure assessment and epidemiological research related to this critical environmental challenge.

Leaf water relations determine the trade-off between ozone resistance and stomatal functionality in urban tree species

Urban trees possess different capacities to mitigate ozone (O3) pollution through stomatal uptake. Stomatal closure protects trees from oxidative damage but limits their growth. To date, it is unclear how plant hydraulic function affect stomatal behaviour and determine O3 resistance. We assessed gas exchange and hydraulic traits in three subtropical urban tree species, Celtis sinensis, Quercus acutissima, and Q. nuttallii, under nonfiltered ambient air (NF) and elevated O3 (NF60). NF60 decreased photosynthetic rate (An) and stomatal conductance (gs) only in Q. acutissima and Q. nuttallii. Maintained An in C. sinensis suggested high O3 resistance and was attributed to higher leaf capacitance at the full turgor. However, this species exhibited a reduced stomatal sensitivity to vapour pressure deficit and an increased minimal gs under NF60. Such stomatal dysfunction did not decrease intrinsic water use efficiency (WUE) due to a tight coupling of An and gs. Conversely, Q. acutissima and Q. nuttallii showed maintained stomatal sensitivity and increased WUE, primarily correlated with gs and leaf water relations, including relative water content and osmotic potential at turgor loss point. Our findings highlight a trade-off between O3 resistance and stomatal functionality, with efficient stomatal control reducing the risk of hydraulic failure under combined stresses.

Association of ambient ozone exposure and greenness exposure with hemorrhagic stroke mortality at different times: A cohort study in Shandong Province, China

Evidence on the association between long-term ozone exposure and greenness exposure and hemorrhagic stroke (HS) is limited, with mixed results. One potential source of this inconsistency is the difference in exposure time metrics. This study aimed to investigate the association between long-term exposure to ambient ozone, greenness, and mortality from HS using exposure metrics at different times. We also examined whether greenness exposure modified the relationship between ozone exposure and mortality due to HS. The study population consisted of 45771 participants aged ≥40 y residing in 20 counties in Shandong Province who were followed up from 2013 to 2019. Ozone exposure metrics (annual mean and warm season) and the normalized difference a measure of greenness exposure, were calculated. The relationship between environmental exposures (ozone and greenness exposures) and mortality from HS was assessed using time-dependent Cox proportional hazards models, and the modification of greenness exposure was examined using stratified analysis with interaction terms. The person-years at the end of follow-up were 90,663. With full adjustments, the risk of death from hemorrhagic stroke increased by 5% per interquartile range increase in warm season ozone [hazard ratio =1.05; 95 % confidence interval: 1.01-1.08]. No clear association was observed between annual ozone and mortality HS. Both the annual and summer NDVI were found to reduce the risk of HS mortality. The relationships were influenced by age, sex, and residence (urban or rural). Furthermore, greenness exposure was shown to have a modifying effect on the relationship between ozone exposure and the occurrence of HS mortality (P for interaction = 0.001). Long-term exposure to warm season O3 was positively associated with HS mortality, while greenness exposure was inversely associated with HS mortality. Greenness exposure may mitigate the negative effects of warm season ozone exposure on HS mortality.

Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models

In Great Britain, limited studies have employed machine learning methods to predict air pollution especially ozone (O3) with high spatiotemporal resolution. This study aimed to address this gap by developing random forest models for four key pollutants (fine and inhalable particulate matter [PM2.5 and PM10], nitrogen dioxide [NO2] and O3) by integrating multiple-source predictors at a daily level and 1-km resolution. The out-of-bag R2 (root mean squared error, RMSE) between predictions from models and measurements from monitoring stations in 2006-2013 was 0.85 (3.63 μg/m3) for PM2.5, 0.77 (6.00 μg/m3) for PM10, 0.85 (9.71 μg/m3) for NO2, and 0.85 (9.39 μg/m3) for maximum daily 8-h average (MDA8) O3 at daily level, and the predicting accuracy was higher at monthly and annual level. The high-resolution predictions captured characterized spatiotemporal patterns of the four pollutants. Higher concentrations of PM2.5, PM10, and NO2 were distributed in densely populated southern regions of Great Britain while O3 showed an inverse spatial pattern in general, which could not be fully depicted by monitoring stations. Therefore, predictions produced in this study could improve exposure assessment with less exposure misclassification and flexible exposure windows for future epidemiological studies to investigate the impact of air pollution across Great Britain.

Association between long-term ozone exposure and readmission for chronic obstructive pulmonary disease exacerbation

The relationship between long-term ozone (O₃) exposure and readmission for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains elusive. In this study, we collected individual-level information on AECOPD hospitalizations from a standardized electronic database in Guangzhou from January 1, 2014, to December 31, 2015. We calculated the annual mean O₃ concentration prior to the dates of the index hospitalization for AECOPD using patients' residential addresses. Employing Cox proportional hazards models, we assessed the association between long-term O₃ concentration and the risk of AECOPD readmission across several time frames (30 days, 90 days, 180 days, and 365 days). We estimated the disease and economic burden of AECOPD readmissions attributable to O₃ using a counterfactual approach. Of the 4574 patients included in the study, 1398 (30.6%) were readmitted during the study period, with 262 (5.7%) readmitted within 30 days. The annual mean O₃ concentration was 90.3 μg/m3 (standard deviation [SD] = 8.2 μg/m3). A 10-μg/m3 increase in long-term O₃ concentration resulted in a hazard ratio (HR) for AECOPD readmission within 30 days of 1.28 (95% confidence interval [CI], 1.09 to 1.49), with similar results for readmission within 90, 180, and 365 days. Older patients (aged 75 years or above) and males were more susceptible (HR, 1.33; 95% CI, 1.10-1.61 and HR, 1.29; 95% CI, 1.09-1.53, respectively). The population attributable fraction for 30-day readmission due to O₃ exposure was 29.0% (95% CI, 28.4%-30.0%), and the attributable mean cost per participant was 362.3 USD (354.5-370.2). Long-term exposure to elevated O₃ concentrations is associated with an increased risk of AECOPD readmission, contributing to a significant disease and economic burden.

Altered metabolome and microbiome associated with compromised intestinal barrier induced hepatic lipid metabolic disorder in mice after subacute and subchronic ozone exposure

Exposure to ozone has been associated with metabolic disorders in humans, but the underlying mechanism remains unclear. In this study, the role of the gut-liver axis and the potential mechanism behind the metabolic disorder were investigated by histological examination, microbiome and metabolome approaches in mice during the subacute (4-week) and subchronic (12-week) exposure to 0.5 ppm and 2.5 ppm ozone. Ozone exposure resulted in slowed weight gain and reduced hepatic lipid contents in a dose-dependent manner. After exposure to ozone, the number of intestinal goblet cells decreased, while the number of tuft cells increased. Tight junction protein zonula occludens-1 (ZO-1) was significantly downregulated, and the apoptosis of epithelial cells increased with compensatory proliferation, indicating a compromised chemical and physical layer of the intestinal barrier. The hepatic and cecal metabolic profiles were altered, primarily related to lipid metabolism and oxidative stress. The abundance of Muribaculaceae increased dose-dependently in both colon and cecum, and was associated with the decrease of metabolites such as bile acids, betaine, and L-carnitine, which subsequently disrupted the intestinal barrier and lipid metabolism. Overall, this study found that subacute and subchronic exposure to ozone induced metabolic disorder via disturbing the gut-liver axis, especially the intestinal barrier. These findings provide new mechanistic understanding of the health risks associated with environmental ozone exposure and other oxidative stressors.

VAR-tree model based spatio-temporal characterization and prediction of O3 concentration in China

Ozone (O₃) pollution in the atmosphere is getting worse in many cities. In order to improve the accuracy of O₃ prediction and obtain the spatial distribution of O₃ concentration over a continuous period of time, this paper proposes a VAR-XGBoost model based on Vector autoregression (VAR), Kriging method and XGBoost (Extreme Gradient Boosting). China is used as an example and its spatial distribution of O₃ is simulated. In this paper, the O₃ concentration data of the monitoring sites in China are obtained, and then a spatial prediction method of O₃ mass concentration based on the VAR-XGBoost model is established, and finnally its influencing factors are analyzed. This paper concludes that O₃ features the highest correlation with PM_2.5 and the lowest correlation with SO₂. Among the measurement factors, wind speed and temperature are the most important factors affecting O₃ pollution, which are positively correlated to O₃ pollution. In addition, precipitation is negatively correlated with 8-hour ozone concentration. In this paper, the performance of the VAR-XGBoost model is evaluated based on the ten-fold cross-validation method of sample, site and time, and a comparison with the results of XGBoost, CatBoost (categorical boosting), ExtraTrees, GBDT (gradient boosting decision tree), AdaBoost (adaptive boosting), RF (random forest), Decision tree, and LightGBM (light gradient boosting machine) models is conducted. The result shows that the prediction accuracy of the VAR-XGBoost model is better than other models. The seasonal and annual average R² reaches 0.94 (spring), 0.93 (summer), 0.92 (autumn), 0.93 (winter), and 0.95 (average from 2016 to 2021). The data show that the applicability of the VAR-XGBoost model in simulating the spatial distribution of O₃ concentrations in China performs well. The spatial distribution of O₃ concentrations in the Chinese region shows an obvious feature of high in the east and low in the west, and the spatial distribution is strongly influenced by topographical factors. The mean concentration is clearly low in winter and high in summer within a season. The results of this study can provide a scientific basis for the prevention and control of regional O₃ pollution in China, and can also provide new ideas for the acquisition of data on the spatial distribution of O₃ concentrations within cities.

Combined exposure of heat stress and ozone enhanced cognitive impairment via neuroinflammation and blood brain barrier disruption in male rats

BACKGROUND

Heat stress (HS) exposure has been linked to cognitive dysfunction. In reality, high temperature does not occur alone in environment, and ozone (O₃) and heatwaves usually co-exist in atmospheric environment. However, whether O₃ exposure exacerbates HS-induced cognitive impairment and the potential underlying mechanisms have not been explored experimentally. The aim of this study was to determine the co-effects and mechanisms of HS and O₃ on the cognitive dysfunction.

METHODS

48 Sprague Dawley male rats were randomly divided into 4 groups: control, HS, O₃ and HS plus O₃ (HO₃) groups. Rats in HS and HO₃ group were exposed to 40 °C every morning from 9:00 to 12:00 for 15 consecutive days. While rats in O₃ and HO₃ groups were exposed to 0.7 ppm O₃ the same day from 14:00 to 17:00 for 15 days. Cognitive performance was examined with Morris water maze test. Neurodegeneration, glial activation, neuroinflammation, blood brain barrier (BBB) disruption and apoptosis were evaluated by Western blot, Elisa, immunohistochemistry and immunofluorescence staining.

RESULTS

HS induced cognitive decline and neuronal damage in rats. Further studies showed that exposure of rats to HS could also induce glial activation, neuroinflammation and neuronal apoptosis in hippocampus, and decrease in the expressions of ZO-1, claudin-5 and occluding, indicative of BBB disruption. Impressively, the neuronal effects induced by HS, as depicted above, could be worsened by co-exposure to O₃ in rats.

CONCLUSIONS

Co-exposure to O₃ promotes HS-induced cognitive impairment in rats possibly through glial-mediated neuroinflammation and BBB disruption.

A systematic review and meta-analysis of intraday effects of ambient air pollution and temperature on cardiorespiratory morbidities: First few hours of exposure matters to life

BACKGROUND

A growing number of studies have reported an increased risk of cardiovascular disease (CVD) and respiratory disease (RD) within hours after exposure to ambient air pollution or temperature. We assemble published evidence on the sub-daily associations of CVD and RD with ambient air pollution and temperature.

METHODS

Databases of PubMed and Web of Science were searched for original case-crossover and time-series designs of English articles examining the intra-day effects of ambient air pollution [particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), 2.5-10μm (PM_10-2.5), and < 7 μm (SPM), O₃, SO₂, NO₂, CO, and NO] and temperatures (heat and cold) on cardiorespiratory diseases within 24 h after exposure in the general population by comparing with exposure at different exposure levels or periods. Meta-analyses were conducted to pool excess risks (ERs, absolute percentage increase in risk) of CVD and RD morbidities associated with an increase of 10 μg/m³ in particulate matters, 0.1 ppm in CO, and 10 ppb in other gaseous pollutants.

FINDINGS

Final analysis included thirty-three papers from North America, Europe, Oceania, and Asia. Meta-analysis found an increased risk of total CVD morbidity within 3 h after exposure to PM_2.5 [ER%: 2.65% (95% CI: 1.00% to 4.34%)], PM_10-2.5 [0.31% (0.02% to 0.59%)], O₃ [1.42% (0.14% to 2.73%)], and CO [0.41% (0.01% to 0.81%)]. The risk of total RD morbidity elevated at lag 7-12 h after exposure to PM_2.5 [0.69% (0.14% to 1.24%)] and PM₁₀ [0.38% (0.02% to 0.73%)] and at lag 12-24 h after exposure to SO₂ [2.68% (0.94% to 4.44%)]. Cause-specific CVD analysis observed an increased risk of myocardial infarction morbidity within 6 h after exposure to PM_2.5, PM₁₀, and NO₂, and an increased risk of out-of-hospital cardiac arrest morbidity within 12 h after exposure to CO. Risk of total CVD also increased within 24 h after exposure to heat.

INTERPRETATION

This study supports a sudden risk increase of cardiorespiratory diseases within a few hours after exposure to air pollution or heat, and some acute and highly lethal diseases such as myocardial infarction and cardiac arrest could be affected within a shorter time.

FUNDING

The National Natural Science Foundation of China (Grant No. 42105165; 81773518), the High-level Scientific Research Foundation of Anhui Medical University (Grant No. 0305044201), and the Discipline Construction of Anhui Medical University (Grant No. 0301001836).