Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network.

Severe ground-level ozone (O3) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution characteristics of ground-level O3 and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021. Then, a high-performance convolutional neural network (CNN) model was established by expanding the moment and the concentration variations to general factors. Finally, the response mechanism of O3 to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables. The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern. When the wind direction (WD) ranges from east to southwest and the wind speed (WS) ranges between 2 and 3 m/sec, higher O3 concentration prone to occur. At different temperatures (T), the O3 concentration showed a trend of first increasing and subsequently decreasing with increasing NO2 concentration, peaks at the NO2 concentration around 0.02 mg/m3. The sensitivity of NO2 to O3 formation is not easily affected by temperature, barometric pressure and dew point temperature. Additionally, there is a minimum [Formula: see text] at each temperature when the NO2 concentration is 0.03 mg/m3, and this minimum [Formula: see text] decreases with increasing temperature. The study explores the response mechanism of O3 with the change of driving variables, which can provide a scientific foundation and methodological support for the targeted management of O3 pollution.

Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou.

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

Adverse effects of meteorological factors and air pollutants on dry eye disease: a hospital-based retrospective cohort study.

Although previous studies have suggested that meteorological factors and air pollutants can cause dry eye disease (DED), few clinical cohort studies have determined the individual and combined effects of these factors on DED. We investigated the effects of meteorological factors (humidity and temperature) and air pollutants [particles with a diameter ≤ 2.5 µ m (PM2.5), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO)] on DED. A retrospective cohort study was conducted on 53 DED patients. DED was evaluated by Symptom Assessment in Dry Eye (SANDE), tear secretion, tear film break-up time (TBUT), ocular staining score (OSS), and tear osmolarity. To explore the individual, non-linear, and joint associations between meteorological factors, air pollutants, and DED parameters, we used generalized linear mixed model (GLMM) and Bayesian kernel machine regression (BKMR). After adjusting for all covariates, lower relative humidity or temperature was associated with a higher SANDE (p < 0.05). Higher PM2.5, O3, and NO2 levels were associated with higher SANDE and tear osmolarity (p < 0.05). Higher O3 levels were associated with lower tear secretion and TBUT, whereas higher NO2 levels were associated with higher OSS (p < 0.05). BKMR analyses indicated that a mixture of meteorological factors and air pollutants was significantly associated with increased SANDE, OSS, tear osmolarity, and decreased tear secretion.

Examining air pollution exposure dynamics in disadvantaged communities through high-resolution mapping.

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 meters) daily air pollution maps for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California for 2012-2019. Our findings revealed opposite spatial patterns of NO2 and PM2.5 to that of O3. We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO2 and PM2.5 reductions and the advantaged neighborhoods experienced greatest rising O3 concentrations. Further, day-to-day exposure variations decreased for NO2 and O3. The disparity in NO2 exposure decreased, while it persisted for O3. In addition, PM2.5 showed increased day-to-day variations across all communities due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.

Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth's atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis.

BACKGROUND: Wildfire activity is an important source of tropospheric ozone (O3) pollution. However, no study to date has systematically examined the associations of wildfire-related O3 exposure with mortality globally. METHODS: We did a multicountry two-stage time series analysis. From the Multi-City Multi-Country (MCC) Collaborative Research Network, data on daily all-cause, cardiovascular, and respiratory deaths were obtained from 749 locations in 43 countries or areas, representing overlapping periods from Jan 1, 2000, to Dec 31, 2016. We estimated the daily concentration of wildfire-related O3 in study locations using a chemical transport model, and then calibrated and downscaled O3 estimates to a resolution of 0·25°â€ˆ× 0·25° (approximately 28 km2 at the equator). Using a random-effects meta-analysis, we examined the associations of short-term wildfire-related O3 exposure (lag period of 0-2 days) with daily mortality, first at the location level and then pooled at the country, regional, and global levels. Annual excess mortality fraction in each location attributable to wildfire-related O3 was calculated with pooled effect estimates and used to obtain excess mortality fractions at country, regional, and global levels. FINDINGS: Between 2000 and 2016, the highest maximum daily wildfire-related O3 concentrations (≥30 µg/m3) were observed in locations in South America, central America, and southeastern Asia, and the country of South Africa. Across all locations, an increase of 1 µg/m3 in the mean daily concentration of wildfire-related O3 during lag 0-2 days was associated with increases of 0·55% (95% CI 0·29 to 0·80) in daily all-cause mortality, 0·44% (-0·10 to 0·99) in daily cardiovascular mortality, and 0·82% (0·18 to 1·47) in daily respiratory mortality. The associations of daily mortality rates with wildfire-related O3 exposure showed substantial geographical heterogeneity at the country and regional levels. Across all locations, estimated annual excess mortality fractions of 0·58% (95% CI 0·31 to 0·85; 31 606 deaths [95% CI 17 038 to 46 027]) for all-cause mortality, 0·41% (-0·10 to 0·91; 5249 [-1244 to 11 620]) for cardiovascular mortality, and 0·86% (0·18 to 1·51; 4657 [999 to 8206]) for respiratory mortality were attributable to short-term exposure to wildfire-related O3. INTERPRETATION: In this study, we observed an increase in all-cause and respiratory mortality associated with short-term wildfire-related O3 exposure. Effective risk and smoke management strategies should be implemented to protect the public from the impacts of wildfires. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

Age and sex differences in the effects of short- and long-term exposure to air pollution on endothelial dysfunction.

BACKGROUND: The effects of air pollution on endothelial function remain unclear across populations. We aimed to use brachial artery flow-mediated dilatation (FMD) to identify demographic differences in the effects of air pollution exposure on endothelial dysfunction. METHODS: We measured FMD in 850 participants from October 2016 to January 2020. Location-specific concentrations of fine particulate matter < 2.5 µm aerodynamic diameter (PM2.5), inhalable particulate matter < 10 µm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) measured by fixed ambient air monitoring stations were collected for short- and long-term exposure assessment. Multiple linear regression models and restricted cubic splines were used to assess the associations before and after stratification by age and sex. RESULTS: This study eventually included 828 participants [551 (66.5%) younger than 65 years and 553 (66.8%) men]. Each 10 µg/m3 increase in 7-day exposure to PM2.5 and PM10 was significantly linearly associated with a 0.07% (ß = -0.07, 95% CI: -0.13 to -0.004) and 0.05% (ß = -0.05, 95% CI: -0.10 to -0.004) decrease in FMD in the fully adjusted model. After full adjustment, long-term exposure to all air pollutants was significantly associated with impaired FMD. Each 10 µg/m3 increase in long-term exposure to PM2.5 and PM10 was significantly associated with a -0.18% (95% CI: -0.34 to -0.03) and - 0.23% (95% CI: -0.40 to -0.06) change in FMD, respectively. After stratification, the associations of lower FMD with long-term exposure to PM2.5, PM10, SO2, NO2, and CO significantly persisted in men and participants younger than 65 years instead of women or older participants. For short-term exposure, we observed differences consistent with long-term exposure and a stronger effect of 7-day exposure to SO2 in men due to a significant interaction effect. CONCLUSION: Short- and long-term exposure to different air pollutants are strongly associated with decreased endothelial function, and susceptibility to air pollution varies significantly with age and sex.

Sociodemographic Determinants of Extreme Heat and Ozone Risk Among Older Adults in 3 Sun Belt Cities.

BACKGROUND: Vulnerable populations across the United States are frequently exposed to extreme heat, which is becoming more intense due to a combination of climate change and urban-induced warming. Extreme heat can be particularly detrimental to the health and well-being of older citizens when it is combined with ozone. Although population-based studies have demonstrated associations between ozone, extreme heat, and human health, few studies focused on the role of social and behavioral factors that increase indoor risk and exposure among older adults. METHODS: We conducted a household survey that aimed to understand how older adults are affected by extreme heat and ozone pollution inside and outside of their homes across Houston, Phoenix, and Los Angeles. We examine contributing factors to the risk of self-reported health effects using a generalized linear mixed-effects regression model of telephone survey data of 909 older adults in 2017. RESULTS: We found an increased occurrence of self-reported symptoms for extreme heat with preexisting respiratory health conditions and a lack of air conditioning access; self-reported ozone symptoms were more likely with preexisting respiratory health conditions. The risk of heat-related symptoms was slightly higher in Los Angeles than Houston and Phoenix. We found several demographic, housing, and behavioral characteristics that influenced the risk of heat- and ozone-related symptoms. CONCLUSIONS: The increased risk among older adults based on specific social and behavioral factors identified in this study can inform public health policy and help cities tailor their heat and ozone response plans to the specific needs of this vulnerable population.

Study on O3-NOx-VOCs combined air pollution and ozone health effects in the Hexi Corridor.

In order to study the ecological and atmospheric recovery of the Hexi Corridor region, this paper analyzes the migration changes of land use characteristics and utilizes multivariate data and BenMAP-CE software to study the pollution characteristics of ozone and its precursors and the impact on human health in the Hexi Corridor region. The results showed that the increase of cultivated land area in the Hexi Corridor mainly originated from grassland. The MDA8-O3 concentrations met the primary and secondary standards of the Ambient Air Quality Standards on 43% and 99% of the days, respectively. NO2 showed a negative weekend effect with O3, and HCHO was opposite to it. Temperature, barometric pressure, and vegetation were highly correlated with O3-NO2-HCHO. Ozone pollution in the study area caused about 60% of all-cause premature deaths due to cardiovascular diseases. The study suggests that controlling exogenous transport in Wuwei City during the high ozone period (except August) is mainly dominated by the west and northwest, and that synergistic management of VOCs and NOx emissions can reduce O3 pollution and, consequently, reduce the risk to human health.

High-Resolution Modeling of Summertime Biogenic Isoprene Emissions in New York City.

As cities strive for ambitious increases in tree canopy cover and reductions in anthropogenic volatile organic compound (AVOC) emissions, accurate assessments of the impacts of biogenic VOCs (BVOCs) on air quality become more important. In this study, we aim to quantify the impact of future urban greening on ozone production. BVOC emissions in dense urban areas are often coarsely represented in regional models. We set up a high-resolution (30 m) MEGAN (The Model of Emissions of Gases and Aerosols from Nature version 3.2) to estimate summertime biogenic isoprene emissions in the New York City metro area (NYC-MEGAN). Coupling an observation-constrained box model with NYC-MEGAN isoprene emissions successfully reproduced the observed isoprene concentrations in the city core. We then estimated future isoprene emissions from likely urban greening scenarios and evaluated the potential impact on future ozone production. NYC-MEGAN predicts up to twice as much isoprene emissions in NYC as the coarse-resolution (1.33 km) Biogenic Emission Inventory System version 3.61 (BEIS) on hot summer days. We find that BVOCs drive ozone production on hot summer days, even in the city core, despite large AVOC emissions. If high isoprene emitting species (e.g., oak trees) are planted, future isoprene emissions could increase by 1.4-2.2 times in the city core, which would result in 8-19 ppbv increases in peak ozone on ozone exceedance days with current NOx concentrations. We recommend planting non- or low-isoprene emitting trees in cities with high NOx concentrations to avoid an increase in the frequency and severity of future ozone exceedance events.

Association of air pollution with incidence of end-stage kidney disease in two large European cohorts.

End-stage kidney disease (ESKD) poses a high burden on patients and health systems. While numerous studies indicate an association between air pollution and chronic kidney disease, studies on ESKD are rare. We investigated the association of long-term exposure to nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC) and ozone (O3) with ESKD incidence in two large population-based European cohorts. We followed individuals in the Austrian Vorarlberg Health Monitoring and Promotion Program (VHM&PP) and the Italian Rome Longitudinal Study (RoLS) using dialysis and kidney transplant registries. Long-term exposure to pollutants was estimated at the home address using Europe-wide land use regression models at 100x100m scale. Hazard ratios (HR) were determined from Cox-proportional hazard models adjusted for individual and neighbourhood level confounders. We observed 501 events among 136,823 individuals in VHM&PP (mean age 42.1 years; crude incidence rate (IR) 0.14 per 1000 person-years) and 3231 events among 1,939,461 individuals in RoLS (mean age 52.4 years; IR 0.22 per 1000 person-years). In VHM&PP, there was no evidence of an association between PM2.5 or O3 and ESKD. There were elevated HRs but with large confidence intervals for BC (HR 1.17 [95 % confidence interval (CI): 0.98, 1.39] for 0.5*10-5/m), and for NO2 (HR 1.14 [95%CI: 0.96, 1.35] for 10 µg/m3). In RoLS, ESKD was associated with PM2.5 (HR 1.37 [95 % CI: 1.06, 1.76] for an increase of 5 µg/m3), while there was no evidence of association with BC, NO2, or O3 exposure. Our study suggests an association of air pollution with ESKD incidence, which differed between the two cohorts and may possibly be influenced by respective air pollution mixtures.

Multi-source observations on the effect of atmospheric blocking on air quality in Istanbul: a study case.

Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in Istanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in Istanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in Istanbul was determined as "poor" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the Istanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

Toward cleaner air and better health: Current state, challenges, and priorities.

The most up-to-date estimate of the global burden of disease indicates that ambient air pollution, including fine particulate matter and ozone, contributes to an estimated 5.2 million deaths each year. In this review, we highlight the challenges in estimating population exposure to air pollution and attributable health risks, particularly in low- and middle-income countries and among vulnerable populations. To protect public health, the evidence so far confirms urgent needs to prioritize interdisciplinary research on air pollution exposure and risk assessment and to develop evidence-based intervention policies and risk communication strategies. Here, we synthesize the emerging evidence supporting the monitoring and evaluation of the progress in implementation of the Global Air Quality Guidelines prepared by the World Health Organization.

Assessing long-term effects of gaseous air pollution exposure on mortality in the United States using a variant of difference-in-differences analysis.

Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010-1.126) for total mortality, 1.067 (1.009-1.128) for nonaccidental mortality, and 1.125 (1.060-1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

Transformer-based ozone multivariate prediction considering interpretable and priori knowledge: A case study of Beijing, China.

Ozone pollution is the focus of current environmental governance in China and high-quality prediction of ozone concentration is the prerequisite to effective policymaking. The studied ozone pollution time series exhibits distinct seasonality and secular trends and is associated with various factors. This study developed an interpretable hybrid model by combining STL decomposition and the Transformer (STL-Transformer) with the prior information of ozone time series and global multi-source information as prediction basis. The STL decomposition decomposes ozone time series into trend, seasonal, and remainder components. Then, the three components, along with other air quality and meteorological data, are integrated into the input sequence of the Transformer. The experiment results show that the STL-Transformer outperforms the other five state-of-the-art models, including the standard Transformer. Specially, the univariate forecasting for ozone relies on mimicking the patterns and trends that have occurred in the past. In contrast, multivariate forecasting can effectively capture complex relationships and dependencies involving multiple variables. The method successfully grasps the prior and global multi-source information and simultaneously improves the interpretability of ozone prediction with high precision. This study provides new insights for air pollution forecasting and has reliable theoretical value and practical significance for environmental governance.

Traceability and policy suggestions for ozone pollution in heavy industrial city in Northeast China.

In the heavy industrial city of Northeast China, there has been a significant decrease in particulate matter pollution while experiencing a sharp increase in ozone (O3) pollution. However, the main influencing factors and source contributions to O3 remain unclear. Taking the case of Siping as an example, this study analyzed the spatiotemporal characteristics, assessed local source contributions to O3, and revealed regional transmission effects using numeric simulation and statistical methods. Temporally, higher O3 concentrations were observed in summer and the afternoon, with hourly peaks up to 254 µg/m3. Spatially, O3 pollution was mainly contributed by background concentrations (34.52%), external transport (34.50%), and local emissions (30.98%) during the case study period (June 11-18, 2021). Among the local emission sources, biological emissions, the industrial sector, and the traffic sector accounted for 35.30%, 32.09%, and 23.58% of the O3 concentration, respectively. For regional atmospheric transmission, high O3 pollution was accompanied by wind from the southwest directions, and the trajectory of air mass transport suggests that eastern Mongolia, the Korean Peninsula, and its neighboring regions contribute to O3 pollution. Furthermore, sensitivity analysis showed that O3 pollution in Siping is a co-controlled region by anthropogenic volatile organic compounds (AVOCs) and NOX, which implies control in an optimal ratio of VOCs and NOX emissions. Thus, our results highlight the importance of joint prevention and control of O3 pollution in the region, optimization of biogenic landscape ecology, and control of VOCs and NOx in both the industrial and transport sectors.

Spatiotemporal joint analysis of PM2.5 and Ozone in California with INLA approach.

The substantial threat of concurrent air pollutants to public health is increasingly severe under climate change. To identify the common drivers and extent of spatiotemporal similarity of PM2.5 and ozone (O3), this paper proposed a log Gaussian-Gumbel Bayesian hierarchical model allowing for sharing a stochastic partial differential equation and autoregressive model of order one (SPDE-AR(1)) spatiotemporal interaction structure. The proposed model, implemented by the approach of integrated nested Laplace approximation (INLA), outperforms in terms of estimation accuracy and prediction capacity for its increased parsimony and reduced uncertainty, especially for the shared O3 sub-model. Besides the consistently significant influence of temperature (positive), extreme drought (positive), fire burnt area (positive), gross domestic product (GDP) per capita (positive), and wind speed (negative) on both PM2.5 and O3, surface pressure and precipitation demonstrate positive associations with PM2.5 and O3, respectively. While population density relates to neither. In addition, our results demonstrate similar spatiotemporal interactions between PM2.5 and O3, indicating that the spatial and temporal variations of these pollutants show relatively considerable consistency in California. Finally, with the aid of the excursion function, we see that the areas around the intersection of San Luis Obispo and Santa Barbara counties are likely to exceed the unhealthy O3 level for USG simultaneously with other areas throughout the year. Our findings provide new insights for regional and seasonal strategies in the co-control of PM2.5 and O3. Our methodology is expected to be utilized when interest lies in multiple interrelated processes in the fields of environment and epidemiology.

Characteristics of surface ozone pollution and its correlations with meteorological factors: the case of Xiangtan.

Based on ozone (O3) monitoring data for Xiangtan and meteorological observation data for 2020-2022, we examined ozone pollution characteristics and the effects of meteorological factors on daily maximum 8-h average ozone (O3-8h) concentrations in Xiangtan. Thus, we observed significant increases as well as notable seasonal variations in O3-8h concentrations in Xiangtan during the period considered. The ozone and temperature change response slope (KO3-T) indicated that local emissions had no significant effect on O3-8h generation. Further, average O3-8h concentration and maximum temperature (Tmax) values showed a polynomial distribution. Specifically, at Tmax < 27 °C, it increased almost linearly with increasing temperature, and at Tmax between 27 and 37 °C, it showed an upward curvilinear trend as temperature increased, but at a much lower rate. Then, at Tmax > 37 °C, it decreased with increasing temperature. With respect to relative humidity (RH), the average O3-8h concentration primarily exceeded the standard value when RH varied in the range of 45-65%, which is the key humidity range for O3 pollution, and the inflection point for the correlation curve between O3-8h concentration and RH appeared at ~55%. Furthermore, at wind speeds (WSs) below 1.5 m∙s-1, O3-8h concentration increased rapidly, and at WSs in the 1.5-2 m∙s-1 range, it increased at a much faster rate. However, at WSs > 2 m∙s-1, it decreased slowly with increasing WS. O3-8h concentration also showed the tendency to exceed the standard value when the dominant wind directions in Xiangtan were easterly or southeasterly.

Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ.

Short-term exposure to ground-level ozone (O3) poses significant health risks, particularly respiratory and cardiovascular diseases, and mortality. This study addresses the pressing need for accurate O3 forecasting to mitigate these risks, focusing on South Korea. We introduce Deep Bias Correction (Deep-BC), a novel framework leveraging Convolutional Neural Networks (CNNs), to refine hourly O3 forecasts from the Community Multiscale Air Quality (CMAQ) model. Our approach involves training Deep-BC using data from 2016 to 2019, including CMAQ's 72-hour O3 forecasts, 31 meteorological variables from the Weather Research and Forecasting (WRF) model, and previous days' station measurements of 6 air pollutants. Deep-BC significantly outperforms CMAQ in 2021, reducing biases in O3 forecasts. Furthermore, we utilize Deep-BC's daily maximum 8-hour average O3 (MDA8 O3) forecasts as input for the AirQ+ model to assess O3's potential impact on mortality across seven major provinces of South Korea: Seoul, Busan, Daegu, Incheon, Daejeon, Ulsan, and Sejong. Short-term O3 exposure is associated with 0.40 % to 0.48 % of natural cause and respiratory deaths and 0.67 % to 0.81 % of cardiovascular deaths. Gender-specific analysis reveals higher mortality rates among men, particularly from respiratory causes. Our findings underscore the critical need for region-specific interventions to address air pollution's detrimental effects on public health in South Korea. By providing improved O3 predictions and quantifying its impact on mortality, this research offers valuable insights for formulating targeted strategies to mitigate air pollution's adverse effects. Moreover, we highlight the urgency of proactive measures in health policies, emphasizing the significance of accurate forecasting and effective interventions to safeguard public health from the deleterious effects of air pollution.