Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 µg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 µg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing -5-6 µg·m-3 of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Interactions between aerosols and surface ozone in arid and semi-arid regions of China.

Atmospheric aerosols affect surface ozone concentrations by influencing radiation, but the mechanism and dominant factors are unclear. Therefore, this paper analyses the changes in aerosol-radiative-surface ozone in China's arid and semi-arid regions with the help of the Atmospheric Radiative Transfer (SBDART) model. The results suggest that Aerosol Optical Depth (AOD) and coarse Particulate Matter (PM10) have the same trend, with high values in spring and winter and low values in summer and autumn. Surface ozone is high in spring and summer and low in autumn and winter. Surface ozone is higher in spring and summer and lower in autumn and winter. In winter, mainly secondary pollutants are dominated by high pollution levels. In the rest of the seasons, a mixture of dust, motor vehicle exhaust, and soot is dominated by low pollution levels. Surface ozone is positively correlated with fine particles and negatively correlated with coarse particles. Temperature is positively correlated with surface ozone in all seasons and negatively correlated with PM10 in summer, autumn, and winter. Precipitation negatively correlates with PM10 each season and surface ozone in winter and spring. Analysis of surface ozone and PM10 sources in the more polluted city of Hohhot based on the back-line trajectory model showed that airflow trajectories mainly transported surface ozone and PM10 pollution from northwestern Inner Mongolia and western Mongolia. During dusty solid weather, the decrease in radiation reaching the Earth's surface and the cooling effect of aerosols lead to lower temperatures, which slows down the rate of chemical reactions of precursors of surface ozone, resulting in lower ozone concentrations at the surface. This study can provide a theoretical reference for aerosol and surface ozone control in arid and semi-arid areas of China.

Spatiotemporal patterns of surface ozone exposure inequality in China.

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 µg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 µg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

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

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

Drivers of Increasing Ozone during the Two Phases of Clean Air Actions in China 2013-2020.

In response to the severe air pollution issue, the Chinese government implemented two phases (Phase I, 2013-2017; Phase II, 2018-2020) of clean air actions since 2013, resulting in a significant decline in fine particles (PM2.5) during 2013-2020, while the warm-season (April-September) mean maximum daily 8 h average ozone (MDA8 O3) increased by 2.6 µg m-3 yr-1 in China during the same period. Here, we derived the drivers behind the rising O3 concentrations during the two phases of clean air actions by using a bottom-up emission inventory, a regional chemical transport model, and a multiple linear regression model. We found that both meteorological variations (3.6 µg m-3) and anthropogenic emissions (6.7 µg m-3) contributed to the growth of MDA8 O3 from 2013 to 2020, with the changes in anthropogenic emissions playing a more important role. The anthropogenic contributions to the O3 rise during 2017-2020 (1.2 µg m-3) were much lower than that in 2013-2017 (5.2 µg m-3). The lack of volatile organic compound (VOC) control and the decline in nitrogen oxides (NOx) emissions were responsible for the O3 increase in 2013-2017 due to VOC-limited regimes in most urban areas, while the synergistic control of VOC and NOx in Phase II initially worked to mitigate O3 pollution during 2018-2020, although its effectiveness was offset by the penalty of PM2.5 decline. Future mitigation efforts should pay more attention to the simultaneous control of VOC and NOx to improve O3 air quality.

Causal effects of air pollution on mental health among Adults--An exploration of susceptible populations and the role of physical activity based on a longitudinal nationwide cohort in China.

Long-term exposure to air pollutants is likely to be associated with mental disorders, but relevant studies remain limited and inconsistent, and evidence to assess causality is particularly lacking, especially in developing countries. In addition, there are few studies on the role of physical activity in this relationship. We investigated the causal relationship between air pollutant exposure and mental health among Chinese adults and whether physical activity could play a positive role in this relationship. Using the balanced panel data for 2014 and 2016 from the China Family Panel Study, a representative Chinese national cohort study, we selected and validated appropriate instrumental variable to explore the causal relationship between air pollution and mental health and explored the moderating effect of physical activity using an instrumental variable fixed effects model (IVFE) in a counterfactual causal inference framework. PM2.5 and ground surface ozone were selected as proxies for different types of air pollutants and extended the interpretability by studying them for populations with different characteristics. A total of 21,944 participants were included in this study. In the IVFE model, we found that both PM2.5 and ground surface ozone significantly negatively affected mental health, and that habitual physical activity counteracted this negative effect regardless of different types of air pollution. We also found that the findings held for adults with different characteristics. The findings suggest that habitual physical activity may offset the deterioration of mental health in adults in developing countries due to air pollution, regardless of age, gender, income, and the presence of chronic diseases.

Impact assessment of surface ozone exposure on crop yields at three tropical stations over India.

Surface ozone is a damaging pollutant for crops and ecosystems, and the ozone-induced crop losses over India remain uncertain and a topic of debate due to a lack of sufficient observations and uncertainties involved in the modeled results. In this study, we have used the observational data from MAPAN (Modelling Air Pollution And Networking) for the first time to estimate the relative yield losses, crop production losses, and economic losses for the two major crops (wheat and rice). The detailed estimation has been done focusing on three individual suburban sites over India (Patiala, Tezpur, and Delhi) and compared with other related studies over the Indian region. We have used the concentration-based metric (M7, 7-h average from 09:00 to 15:59 h) along with the cumulative ozone exposure indices (AOT40, accumulated exposure over a threshold of 40 ppb) and applied the exposure-response (E-R) functions for the calculation of the crop losses. Our study shows that the yearly crop losses can reach the level of 12.4-40.8% and 2.0-11.1% for the wheat and rice crops, respectively, at certain places like Patiala in India. The annual economic loss can be as high as $4.6 million and $0.7 million for wheat and rice crops, respectively, even at individual locations in India. Our estimated %RYL (relative yield loss) lies in the range of 0.3 + /0.6 times the recent regional model estimates which use only the AOT40 metric. Region-specific E-R functions based on factors suitable for the Indian region needs to be developed.

Exploring drivers of the aggravated surface O3 over North China Plain in summer of 2015-2019: Aerosols, precursors, and meteorology.

Continuous aggravated surface O3 over North China Plain (NCP) has attracted widely public concern. Herein, we evaluated the effects of changes in aerosols, precursor emissions, and meteorology on O3 in summer (June) of 2015-2019 over NCP via 8 scenarios with WRF-Chem model. The simulated mean MDA8 O3 in urban areas of 13 major cities in NCP increased by 17.1%∼34.8%, which matched well with the observations (10.8%∼33.1%). Meanwhile, the model could faithfully reproduce the changes in aerosol loads, precursors, and meteorological conditions. A relatively-even O3 increase (+1.2%∼+3.9% for 24-h O3 and +1.0%∼+3.8% for MDA8 O3) was induced by PM2.5 dropping, which was consistent with the geographic distribution of regional PM2.5 reduction. Meanwhile, the NO2 reduction coupled with a near-constant VOCs led to the elevated VOCs/NOx ratios, and then caused O3 rising in the areas under VOCs-limited regimes. Therein, the pronounced increases occurred in Handan, Xingtai, Shijiazhuang, Tangshan, and Langfang (+10.7%∼+13.6% for 24-h O3 and +10.2%∼+12.2% for MDA8 O3); while the increases in other cities were 5.7%∼10.5% for 24-h O3 and 4.9%∼9.2% for MDA8 O3. Besides, the meteorological fluctuations brought about the more noticeable O3 increases in northern parts (+12.5%∼+13.5% for 24-h O3 and +11.2%∼+12.4% for MDA8 O3) than those in southern and central parts (+3.2%∼+9.3% for 24-h O3 and +3.7%∼+8.8% for MDA8 O3). The sum of the impacts of the three drivers reached 16.7%∼21.9%, which were comparable to the changes of the observed O3. Therefore, exploring reasonable emissions-reduction strategies is essential for the ozone pollution mitigation over this region.

Spatial Resolved Surface Ozone with Urban and Rural Differentiation during 1990-2019: A Space-Time Bayesian Neural Network Downscaler.

Long-term exposure to ambient ozone (O3) can lead to a series of chronic diseases and associated premature deaths, and thus population-level environmental health studies hanker after the high-resolution surface O3 concentration database. In response to this demand, we innovatively construct a space-time Bayesian neural network parametric regressor to fuse TOAR historical observations, CMIP6 multimodel simulation ensemble, population distributions, land cover properties, and emission inventories altogether and downscale to 10 km × 10 km spatial resolution with high methodological reliability (R2 = 0.89-0.97, RMSE = 1.97-3.42 ppbV), fair prediction accuracy (R2 = 0.69-0.77, RMSE = 5.63-7.97 ppbV), and commendable spatiotemporal extrapolation capabilities (R2 = 0.62-0.76, RMSE = 5.38-11.7 ppbV). Based on our predictions in 8-h maximum daily average metric, the rural-site surface O3 are 15.1±7.4 ppbV higher than urban globally averaged across 30 historical years during 1990-2019, with developing countries being of the most evident differences. The globe-wide urban surface O3 are climbing by 1.9±2.3 ppbV per decade, except for the decreasing trends in eastern United States. On the other hand, the global rural surface O3 tend to be relatively stable, except for the rising tendencies in China and India. Using CMIP6 model simulations directly without urban-rural differentiation will lead to underestimations of population O3 exposure by 2.0±0.8 ppbV averaged over each historical year. Our original Bayesian neural network framework contributes to the deep-learning-driven environmental studies methodologically by providing a brand-new feasible way to realize data fusion and downscaling, which maintains high interpretability by conforming to the principles of spatial statistics without compromising the prediction accuracy. Moreover, the 30-year highly spatial resolved monthly surface O3 database with multiple metrics fills in the literature gap for long-term surface O3 exposure tracing.

Surface ozone trends at El Arenosillo observatory from a new perspective.

Surface ozone trends observed at El Arenosillo observatory for the last 22 years (2000-2021) were investigated. The trends for daily averages and daily 5th and 95th percentiles were 1.2 ± 0.3 ppb decade-1, 2.2 ± 0.3 ppb decade-1 and -0.03 ± 0.43 ppb decade-1, respectively, thus showing a significant increase of background ozone. The surface temperature trends were also explored, obtaining trends of 0.5 ± 0.2 °C decade-1, 1.1 ± 0.2 °C decade-1 and -0.3 ± 0.2 °C decade-1 for daily averages, 5th and 95th percentiles, respectively. To identify potential changes in the ozone drivers, the weather pattern shifts were analyzed through the horizontal distribution trends of temperature at 2 m and geopotential height at 850 hPa. A strengthening of the Azores anticyclone and a regional warming were detected, which could contribute to the ozone trends obtained. The surface ozone trend in every month was explored, identifying a monthly pattern, with remarkable opposite trends in December-January (2.4 ± 0.9 ppb decade-1) vs July-August (-0.5 ± 1.1 ppb decade-1). The surface ozone trends for every hour of the day were also explored, identifying two clear patterns. The first pattern occurred from spring to autumn and was characterized by a behavior opposite to the typical daily ozone cycle. The second pattern was observed in winter, and it shows two relative peaks in the ozone trends (around 13:00 and 19:00 UTC). In a context of ozone precursor's depletion, changes in the weather conditions and warmer climate, to improve our knowledge of the ozone trends, we suggest exploring them based on daily and hourly averages.

Anthropogenic drivers of 2013-2017 trends in summer surface ozone in China.

Observations of surface ozone available from ∼1,000 sites across China for the past 5 years (2013-2017) show severe summertime pollution and regionally variable trends. We resolve the effect of meteorological variability on the ozone trends by using a multiple linear regression model. The residual of this regression shows increasing ozone trends of 1-3 ppbv a-1 in megacity clusters of eastern China that we attribute to changes in anthropogenic emissions. By contrast, ozone decreased in some areas of southern China. Anthropogenic NOx emissions in China are estimated to have decreased by 21% during 2013-2017, whereas volatile organic compounds (VOCs) emissions changed little. Decreasing NOx would increase ozone under the VOC-limited conditions thought to prevail in urban China while decreasing ozone under rural NOx-limited conditions. However, simulations with the Goddard Earth Observing System Chemical Transport Model (GEOS-Chem) indicate that a more important factor for ozone trends in the North China Plain is the ∼40% decrease of fine particulate matter (PM2.5) over the 2013-2017 period, slowing down the aerosol sink of hydroperoxy (HO2) radicals and thus stimulating ozone production.

Low sensitivity of Pinus mugo to surface ozone pollution in the subalpine zone of continental Europe.

High altitudes have been exposed to enhanced levels of surface ozone (O3) concentrations over recent decades compared to the pre-industrial era. The responses of vegetation to this toxic pollutant are species-specific and depend on the climate conditions. In this paper, we explored the reaction of Pinus mugo (P. mugo) to O3-induced stress in the continental climate of an ozone-rich mountain area in the High Tatra Mountains (Western Carpathians). The effects of O3 doses modelled by a deposition model, O3 concentrations and other factors on P. mugo were identified from (a) satellite-based data via NDVI (normalised differenced vegetation index) over 2000-2020 and (b) visible injury on needle samples gathered from P. mugo individuals at ground-truth sites in 2019 and 2020. Analysing the NDVI trend, we observed non-significant changes (p > 0.05) in the greenness of P. mugo despite growing in an environment with the average seasonal O3 concentration around 51.6 ppbv, the maximum hourly concentrations more than 90 ppbv and increasing trend of O3 doses by 0.1 mmol m-2 PLA (plant leaf area) year-1. The visible O3 injury of samples collected at study sites was low (mean injury observed on 1-10% of needles' surface), and the symptoms of injury caused by other biotic and abiotic factors prevailed over those caused by O3. In addition, the correlation analyses between NDVI and the climatic factors indicated a significant (p < 0.05) and positive relationship with photosynthetic active radiation (R = 0.45) in July, and with stomatal conductance (R = 0.52) and temperature factor (R = 0.43) in August. Therefore, we concluded that the positive effect of climate conditions, which support the growth processes of P. mugo, may suppress the negative effect of the mean O3 doses of 17.8 mmol m-2 PLA accumulated over the growing season.

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.

Apportionment of long-term trends in different sections of total ozone column over tropical region.

The additive time-series decomposition analysis was performed on National Oceanic and Atmospheric Administration Solar Backscatter Ultraviolet Instrument Merge satellite dataset version 8.6 for the period January 1979 to December 2019 with an objective to detect and apportion long-term trends present in the total ozone column (TOC) and the long-term trends exist in the respective ozone contents present in the vertical sub-columns constituting the TOC viz. upper, middle and lower stratosphere as well as near-surface for the tropical region. Linear regression analysis was performed on the deseasonalized monthly mean time series of TOC and corresponding ozone contents present in each partitioned layer for three different time spans, viz. 1979-2019 (complete time series), 1979-1998 (pre-inflection years), and 1999-2019 (post-inflection years), where 1998 was taken as inflection year. For the complete time-series, statistically significant negative trends were observed in TOC and corresponding ozone contents in the sub-columns over most of the tropical region. Expectedly, during pre-inflection years, strong negative trends were noted for TOC and ozone contents in the partitioned vertical layers. In contrast, during the post-inflection year time span, long-term trends in TOC were statistically insignificant over two-third of the tropical region, but one-third of the subtropical region exhibited negative trends in TOC. During this time span, positive trends were observed in the ozone contents present in the upper stratospheric sub-column. However, negative trends in ozone contents persisted in the middle and the lower stratosphere. It was interesting to note that the ozone contents confined in near-surface layer manifested strong negative trends during pre-inflection years and the same reversed into strong positive trends that in post-inflection span. The observed, contrasting, long-term trends and variability in the respective partitioned layer of the TOC confounded any clear sign of recovery in the TOC over the tropical region. The continuation of declining trends in the middle stratosphere and increasing trends in the near-surface layer of ozone contents is a matter of concern.

Impact of aerosols on surface ozone during COVID-19 pandemic in southern India: A multi-instrumental approach from ground and satellite observations, and model simulations.

The World Health Organization (WHO) declared the coronavirus disease of 2019 (COVID-19) as a pandemic due to its widespread global infection. This has resulted in lockdown under different phases in many nations, including India, around the globe. In the present study, we report the impact of aerosols on surface ozone in the context of pre-lockdown (01st - 24th March 2020 (PLD)), lockdown phase1 (25th March to 14th April 2020 (LDP1)), and lockdown phase 2 (15th April to 03rd May 2020 (LDP2)) on clear days at a semi-arid site, Anantapur in southern India using both in situ observations and model simulations. Collocated measurements of surface ozone (O3), aerosol optical depth (AOD), black carbon mass concentration (BC), total columnar ozone (TCO), solar radiation (SR), and ultraviolet radiation (UV-A) data were collected using an Ozone analyzer, MICROTOPS sunphotometer, Ozonometer, Aethalometer, and net radiometer during the study period. The diurnal variations of O3 and BC exhibited an opposite trend during three phases. The concentrations of ozone were ~10.7% higher during LDP1 (44.8 ± 5.2 ppbv) than the PLD (40.5 ± 6.0 ppbv), which mainly due to an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. The prominent increase in the surface zone during LDP1 is reasonably consistent with the observed photolysis frequencies (j (O1D)) through Tropospheric Ultraviolet and Visible (TUV) model. The results show that a pronounced spectral and temporal variability in the AOD during three lockdown phases is mainly due to distinct aerosol sources. The increase in AOD during LDP2 due to long-range transport can bring large amounts of mineral dust and smoke aerosols from the west Asian region and central India, and which is reasonably consistent with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire counts analysis over the measurement location. Overall, a drastic reduction in BC concentration (~8.4%) and AOD (10.8%) were observed in the semi-arid area during LDP1 with correspondence to PLD. The columnar aerosol size distributions retrieved from the spectral AODs followed power-law plus unimodal during three phases. The absorption angstrom exponent (AAE) analysis reveals a predominant contribution to the BC from biomass burning activities during the lockdown period over the measurement location.

Distinct spatiotemporal variation patterns of surface ozone in China due to diverse influential factors.

A better knowledge of surface ozone variations and the relevant influential factors is of great significance for controlling frequent ozone pollution events. In this study, we first examined the primary variation patterns of surface ozone in space and time across China via a clustering analysis on the basis of daily maximum 8h average surface ozone (MDA8) between 2015 and 2018. Statistical models were then established between MDA8 and a set of influential factors to pinpoint dominant factors contributing to regional MDA8 variations. The clustering results revealed four typical variation patterns of MDA8 in China given distinct pollution levels, seasonality, and long-term trends. Statistical modeling results indicated that the seasonal variability of MDA8 was closely associated with UV radiation and meteorological factors like boundary layer height, temperature and relative humidity. In contrast, the long-term trends of MDA8 were largely linked to ozone precursors and meteorological variables including temperature, relative humidity, and total cloud cover. Moreover, the phenomenal increasing trends of MDA8 in North China were found to be statistically associated with the depletion of nitrogen dioxide (NO2) and carbon monoxide (CO). Specifically, substantial increases in volatile organic compounds (VOCs) along with depletions in NO2 and CO significantly boosted the photochemical ozone formation chain process in a VOC-limited regime like the North China plain. Overall, the inferred linkage in this study provides evidence and clues to help control increasing ozone pollution events in North China.

A WRF-Chem model-based future vehicle emission control policy simulation and assessment for the Beijing-Tianjin-Hebei region, China.

Using 2025 as the target year, we quantitatively assessed the reduction potentials of emissions of primary pollutants (including CO, HC, NOx, PM2.5 and PM10) under different vehicle control policies and the impacts of vehicle emission control policies in the BTH region on the regional PM2.5 concentration in winter and the surface ozone (O3) concentration in summer. Comparing the different scenarios, we found that (1) vehicle control policies will bring significant reductions in the emissions of primary pollutants. Among the individual policies, upgrading new vehicle emission standards and fuel quality in Beijing, Tianjin, and Hebei will be the most effective policy, with emission reductions of primary pollutants of 26.3%-54.7%, 38.0%-70.3% and 46.0%-81.6% in 2025, respectively; (2) for PM2.5 in winter, the Combined Scenario (CS) will lead to a reduction of 0.5-3.9 µg m-3 (3.5%-11.6%) for the monthly average PM2.5 concentrations in most areas. The monthly nitrate and ammonium concentrations would reduce by 5.8% and 5.3%, respectively, in the whole BTH region, indicating that vehicle emission control policies may play an important role in the reduction of PM2.5 concentrations in winter, especially for nitrate aerosols; and (3) for O3 concentrations in summer, vehicle emission control policies will lead to significant decreases. Under the CS scenario, the maximum reduction of monthly average O3 concentrations in the summer is approximately 3.6 ppb (5.9%). Most areas in the BTH region have a decrease of 15 ppb (7.5%) in peak values compared to the base scenario. However, in some VOC-sensitive areas in the BTH region, such as the southern urban areas, significant reductions in NOx may lead to increases in ozone concentrations. Our results highlight that season- and location-specific vehicle emission control measures are needed to alleviate ambient PM2.5 and O3 pollution effectively in this region due to the complex meteorological conditions and atmospheric chemical reactions.

Mutual relationship between surface atmospheric pollutants and CG lightning in Tehran area.

The mutual relationship between surface atmospheric pollutants and Cloud-to-Ground (CG) lightning is studied in the Tehran area for the first time. The impact of surface pollutant concentration of PM10 on CG lightning initiation, as well as the production of NO2 and surface ozone derived by lightning occurrence is investigated. To proceed, the reports of thunderstorm occurrence, including CG lightning in the Tehran area have been collected for years of study from the Iran meteorological organization (IRIMO). The surface pollution data are obtained from the Air Quality Control Center (AQCC) for several stations in the area of interest. The number of lightning (NoL) associated with the selected dates is obtained using the World Wide Lightning Location Network (WWLLN). The correlation coefficients associated with the CG lightning and the concentrations of PM10, NO2, and surface ozone are calculated. The hourly variations of accumulated NoL and NO2 and surface ozone are also compared for 24 hours before and after the lightning activity for four days of study during the years of 2009-2013. The results show that there is a positive correlation between PM10 concentration and lightning flash number, obtained from observational data of WWLLN. Moreover, the comparison of NoL and surface pollutant concentration indicates a clear positive contribution from CG lightning in NO2 and ozone production. In days with a considerable number of lightning occurrences, the comparison of the hourly average of NO2 and O3 concentrations with the lightning flash number reveals that NO2 decreases, and O3 increases due to the significant increases of lightning strikes.

Meteorological mechanism for a large-scale persistent severe ozone pollution event over eastern China in 2017.

An intensive and persistent regional ozone pollution event occurred over eastern China from 25 June to 5 July 2017. 73 out of 96 selected cities, most located in the Beijing-Tianjin-Hebei and the surrounding area (BTHS), suffered severe ozone pollution. A north-south contrast ozone distribution, with higher ozone (199 ± 33 µg/m3) in the BTHS and lower ozone (118 ± 25 µg/m3) in the Yangtze River Delta (YRD), was found to be dominated by the position of the West Pacific Subtropical High (WPSH) and mid-high latitude wave activities. In the BTHS, the positive anomalies of geopotential height at 500 hPa and temperature at the surface indicated favorable meteorological conditions for local ozone formation. Prevailing northwesterly winds in the mid-high troposphere and warm advection induced by weak southerly winds in the low troposphere resulted in low-moderate relative humidity (RH), less total cloud cover (TCC), strong solar radiation and high temperatures. Moreover, southerly winds prevailing over the BTHS aggravated the pollution due to regional transportation of O3 and its precursors. On one hand, the deep sinking motion and inversion layer suppressed the dispersion of pollutants. On the other hand, O3-rich air in the upper layer was maintained at night due to temperature inversion, which facilitated O3 vertical transport to the surface in the next-day morning due to elevated convection. Generally, temperature, UV radiation, and RH showed good correlations with O3 in the BTHS, with rates of 8.51 (µg/m3)/°C (within the temperature range of 20-38°C), 59.54 (µg/m3)/(MJ/m2) and -1.93 (µg/m3)/%, respectively.