Assessing Spatial and Temporal Patterns of Observed Ground-level Ozone in China

Effects of climate change and ozone on vegetation phenology on the Tibetan Plateau

The vegetation phenology, encompassing the start (SOS) and end (EOS) of the growing season on the Tibetan Plateau, has been significantly impacted by global climate change. Furthermore, ozone (O3) has gradually become the main pollutant in this region, substantially influencing carbon cycle and ecosystems on Earth. While ongoing studies have focused mainly on the implications of climate parameters, including temperature, precipitation, and radiation, the effects of O3 on the SOS and EOS remain unclear. Here, we compared the responses and sensitivities of the SOS and EOS to both climatic factors and O3 in this region. With the use of partial correlation analysis, we found that increased precipitation was the most important factor influencing the SOS and caused earlier occurrence (4.8 % vs. 21.9 %) for most plant functional types. In comparison, temperature only dominated in shrublands. In particular, we found that the EOS responded comparably to climatic factors with similar proportions between advancing and delaying patterns. However, higher O3 levels consistently advanced the EOS for almost all plant functional types and was the main factor controlling EOS variations based on the sensitivity analysis. Our results emphasized that O3 pollution should be considered for obtaining better phenological forecasts and determining the impacts of the environment and atmospheric composition on carbon sequestration in terrestrial ecosystems.

Parsimonious estimation of hourly surface ozone concentration across China during 2015-2020

Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015-2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.

Long-term variations in surface ozone at the Longfengshan Regional Atmosphere Background Station in Northeast China and related influencing factors

Surface ozone (O3) is a crucial air pollutant that affects air quality, human health, agricultural production, and climate change. Studies on long-term O3 variations and their influencing factors are essential for understanding O3 pollution and its impact. Here, we conducted an analysis of long-term variations in O3 during 2006-2022 at the Longfengshan Regional Atmosphere Background Station (LFS; 44.44°N, 127.36°E, 330.5 m a.s.l.) situated on the northeastern edge of the Northeast China Plains. The maximum daily 8-h average (MDA8) O3 fluctuated substantially, with the annual MDA8 decreasing significantly during 2006-2015 (-0.62 ppb yr-1, p < 0.05), jumping during 2015-2016 and increasing clearly during 2020-2022. Step multiple linear regression models for MDA8 were obtained using meteorological variables, to decompose anthropogenic and meteorological contributions to O3 variations. Anthropogenic activities acted as the primary drivers of the long-term trends of MDA8 O3, contributing 73% of annual MDA8 O3 variability, whereas meteorology played less important roles (27%). Elevated O3 at LFS were primarily associated with airflows originating from the North China Plain, Northeast China Plain, and coastal areas of North China, primarily occurring during the warm months (May-October). Based on satellite products of NO2 and HCHO columns, the O3 photochemical regimes over LFS revealed NOx-limited throughout the period. NO2 increased first, reaching peak in 2011, followed by substantial decrease; while HCHO exhibited significant increase, contributing to decreasing trend in MDA8 O3 during 2006-2015. The plateauing NO2 and decreasing HCHO may contribute to the increase in MDA8 O3 in 2016. Subsequently, both NO2 and HCHO exhibited notable fluctuations, leading to significant changes in O3. The study results fill the gap in the understanding of long-term O3 trends in high-latitude areas in the Northeast China Plain and offer valuable insights for assessing the impact of O3 on crop yields, forest productivity, and climate change.

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.

Spatio-temporal disparities of Clonorchis sinensis infection in animal hosts in China: a systematic review and meta-analysis

BACKGROUND

Clonorchis sinensis, one of the most important food-borne zoonotic trematodes, remains prevalent in China. Understanding its infection status in animals is crucial for controlling human clonorchiasis. Here we conducted a systematic review and meta-analysis to focus on the spatio-temporal disparities of C. sinensis infection in animals in China.

METHODS

Data on C. sinensis prevalence in snails, the second intermediate hosts, or animal reservoirs in China were extracted from electronic databases including PubMed, Embase, Web of Science, Chinese Wanfang database, CNKI, VIP, and China Biomedical Literature database. A random-effects meta-analysis model was utilized to estimate the pooled prevalence in each of the above animal hosts. Subgroup analysis and multivariable meta-regression were performed to explore potential sources of heterogeneity across studies and compare the temporal disparity of infection rates between high and low epidemic areas. Scatter plots were used to depict the biogeographical characteristics of regions reporting C. sinensis infection in animals.

RESULTS

The overall pooled prevalence of C. sinensis was 0.9% (95% CI: 0.6-1.2%) in snails, 14.2% (12.7-15.7%) in the second intermediate host, and 14.3% (11.4-17.6%) in animal reservoirs. Prevalence in low epidemic areas (with human prevalence < 1%) decreased from 0.6% (0.2-1.2%) before 1990 to 0.0% (0.0-3.6%) after 2010 in snails (P = 0.0499), from 20.3% (15.6-25.3%) to 8.8% (5.6-12.6%) in the second intermediate hosts (P = 0.0002), and from 18.3% (12.7-24.7%) to 4.7% (1.0-10.4%) in animal reservoirs. However, no similar decrease in prevalence was observed in high epidemic areas (with human prevalence ≥ 1.0%). C. sinensis infections were predominantly reported in areas with altitudes below 2346 m and annual cumulative precipitation above 345 mm and were mostly concentrated in eastern China.

CONCLUSIONS

There are spatio-temporal disparities in the animal infections of C. sinensis in different areas of China. Animal infections are primarily concentrated in regions with low altitude and high precipitation. The results suggest that implementing One Health-based comprehensive measures targeting both humans and animals, especially in high epidemic areas, is essential for successful eradication of C. sinensis in China.

First insight into seasonal variability of urban air quality of northern Pakistan: An emerging issue associated with health risks in Karakoram-Hindukush-Himalaya region

There is a dire need of air quality monitoring in the high-mountain areas of Karakoram-Hindu Kush-Himalaya (HKH) region, particularly related to the recent activities undergoing the China-Pakistan Economic Corridor (CPEC). This study presents the first baseline monitoring and evaluation findings from Gilgit city, Gilgit-Baltistan. Hourly data collection for air quality parameters (PM_2.5, NO, NO₂, SO₂, O₃ and CO) were measured using air-pointer (recordum, Austria) from 1 Jan 2018 to 31 Mar 2018 (winter) and 1 Jun 2018 to 31 Aug 2018 (summer). Our findings depict PM_2.5 health limits were crossed in the winter season, while NO, NO₂ and SO₂ remained below their health limits. O₃ and CO showed a rising trend in summer months, crossing the 8-h health limits during the season. Seasonal correlation in meteorology found an inverse relationship between most parameters and temperatures; reverse was true for O₃ and CO. In parallel, thermal optical carbon analysis filter-based sampling characterized air quality into mass concentrations of PM_2.5, organic carbon (OC), elemental carbon (EC) and various heavy metals. Filter-based PM_2.5 correlated well with analyzer-based PM_2.5 for all months that were studied, except February and March 2018. PM_2.5, OC and EC were higher in summer as compared to winter, whereas higher heavy metal contributions were measured predominantly during summer. Health impacts were found to be above health limits for Ni in children only. Furthermore, principal component analysis-multiple linear regression (PCA-MLR) technique was applied to determine source apportionment, confirming the role of biomass burning in winters, and vehicular emissions in summers, highlighting the need for flexible monitoring of technologies/approaches, and communications among the various public, private agencies, and all relevant stakeholders.

Association of ambient air pollution exposure and its variability with subjective sleep quality in China: A multilevel modeling analysis

Growing epidemiological evidence has shown that exposure to ambient air pollution contributes to poor sleep quality. However, whether variability in air pollution exposure affects sleep quality remains unclear. Based on a large sample in China, this study linked individual air pollutant exposure levels and temporal variability with subjective sleep quality. Town-level data on daily air pollution concentration for 30 days prior to the survey date were collected, and the monthly mean value, standard deviations, number of heavily polluted days, and trajectory for six common pollutants were calculated to measure air pollution exposure and its variations. Sleep quality was subjectively assessed using the Pittsburgh Sleep Quality Index (PSQI), and a PSQI score above 5 indicated overall poor sleep quality. Multilevel and negative control models were used. Both air pollution exposure and variability contributed to poor sleep quality. A one-point increase in the one-month mean concentration of particulate matter with aerodynamic diameters of ≤2.5 μm (PM_2.5) and ≤10 μm (PM₁₀) led to 0.4% (95% confidence interval (CI): 1.002-1.006) and 0.3% (95% CI: 1.001-1.004) increases in the likelihoods of overall poor sleep quality (PSQI score >5), respectively; the odds ratios of a heavy pollution day with PM_2.5 and PM₁₀ were 2.2% (95% CI: 1.012-1.032) and 2.2% (95% CI: 1.012-1.032), respectively. Although the mean concentrations of nitrogen dioxide, sulfur dioxide, and carbon monoxide met the national standard, they contributed to the likelihood of overall poor sleep quality (PSQI score >5). A trajectory of air pollution exposure with maximum variability was associated with a higher likelihood of overall poor sleep quality (PSQI score >5). Subjective measures of sleep latency, duration, and efficiency (derived from PSQI) were affected in most cases. Thus, sleep health improvements should account for air pollution exposure and its variations in China under relatively high air pollution levels.

Chemical reactivity of volatile organic compounds and their effects on ozone formation in a petrochemical industrial area of Lanzhou, Western China

Measurements of ozone (O₃) and its precursors were performed in the summer of 2019 in Lanzhou, a petrochemical industrial city, to better understand the reactivity of volatile organic compounds (VOCs) and their effects on O₃ production. During the campaign, the daily maximum 8-hour average (MDA8) O₃, NO₂, and total VOC (TVOC) concentrations reached 72.2 ± 19.9 ppb, 24.9 ± 10.8 ppb, and 50.8 ± 46.1 ppb, respectively. Alkanes, alkenes, halocarbons, aromatics, and alkynes contributed 45.3%, 24.0%, 16.5%, 10.0%, and 4.2% to TVOCs, respectively. The OH reactivity and relative incremental reactivity (RIR) of VOCs at different times were calculated. The results indicated that alkenes played a predominant role, accounting for an average of 68.5% of the initial VOC reactivity. Compared to other regions, alkenes are relatively more important for O₃ formation in the petrochemical industry area of Lanzhou, while aromatics are relatively less important. Generally, O₃ formation occurred in a VOC-limited regime in the morning and in a transitional regime in the afternoon. The response surface methodology (RSM) combined with a chemical box model was applied to obtain relationships between O₃ and its precursors and determine the most effective way to reduce the O₃ concentration. Reduction in the non-alkene concentration slightly affected the O₃ concentration. In contrast, the effect of nitrogen oxides (NO_x) was closely related to the alkene concentration, and NO_x concentration reduction could lead to an increase in the O₃ concentration when alkenes were abated to less than 80% of the present concentration. To mitigate O₃ pollution near the petrochemical industrial area of Lanzhou, reducing the alkene concentration, especially the C4 alkene concentration (1,3-butadiene, cis-2-butene, and trans-2-butene), was the fastest and most effective control strategy. The results of this study serve as a reference for O₃ pollution control in petrochemical industrial areas.

An Ensemble Model-Based Estimation of Nitrogen Dioxide in a Southeastern Coastal Region of China

NO2 (nitrogen dioxide) is a common pollutant in the atmosphere that can have serious adverse effects on the health of residents. However, the existing satellite and ground observation methods are not enough to effectively monitor the spatiotemporal heterogeneity of near-surface NO2 concentrations, which limits the development of pollutant remediation work and medical health research. Based on TROPOMI-NO2 tropospheric column concentration data, supplemented by meteorological data, atmospheric condition reanalysis data and other geographic parameters, combined with classic machine learning models and deep learning networks, we constructed an ensemble model that achieved a daily average near-surface NO2 of 0.03° exposure. In this article, a meteorological hysteretic effects term and a spatiotemporal term were designed, which considerably improved the performance of the model. Overall, our ensemble model performed better, with a 10-fold CV R2 of 0.89, an RMSE of 5.62 µg/m3, and an MAE of 4.04 µg/m3. The model also had good temporal and spatial generalization capability, with a temporal prediction R2 and a spatial prediction R2 of 0.71 and 0.81, respectively, which can be applied to a wider range of time and space. Finally, we used an ensemble model to estimate the spatiotemporal distribution of NO2 in a coastal region of southeastern China from May 2018 to December 2020. Compared with satellite observations, the model output results showed richer details of the spatiotemporal heterogeneity of NO2 concentrations. Due to the advantages of using multi-source data, this model framework has the potential to output products with a higher spatial resolution and can provide a reference for downscaling work on other pollutants.

Short-term air quality forecasting model based on hybrid RF-IACA-BPNN algorithm

Despite the apparent improvement in air quality in recent years through a series of effective measures, the concentration of PM_2.5 and O₃ in Chengdu city remains high. And both the two pollutants can cause serious damage to human health and property; consequently, it is imperative to accurately forecast hourly concentration of PM_2.5 and O₃ in advance. In this study, an air quality forecasting method based on random forest (RF) method and improved ant colony algorithm coupled with back-propagation neural network (IACA-BPNN) are proposed. RF method was used to screen out highly correlated input variables, and the improved ant colony algorithm (IACA) was adopted to combine with BPNN to improve the convergence performance. Two datasets based on two different kinds of monitoring stations along with meteorological data were applied to verify the performance of this proposed model and compared with another five plain models. The results showed that the RF-IACA-BPNN model has the minimum statistical error of the mean absolute error, root mean square error, and mean absolute percentage error, and the values of R² consistently outperform other models. Thus, it is concluded that the proposed model is suitable for air quality prediction. It was also detected that the performance of the models for the forecasting of the hourly concentrations of PM_2.5 were more acceptable at suburban station than downtown station, while the case is just the opposite for O₃, on account of the low variability dataset at suburban station.

Response of carbon, nitrogen and phosphorus concentration and stoichiometry of plants and soils during a soybean growth season to O3 stress and straw return in Northeast China

Carbon (C), nitrogen (N) and phosphorus (P) concentrations and stoichiometry play important roles in biogeochemical cycles of the ecosystems, yet it is still unclear how the allocations of C, N and P concentrations and stoichiometry among plant organs and soils related to O3 stress and straw return. Here, a pot experiment was conducted in open top chambers to monitor the response of C, N and P concentrations and stoichiometry of leaves, stems, roots and soils during a growing season (branching, flowering and podding stages) of soybean (Glycine max; a species highly sensitive to O3) to background O3 concentration (44.8 ± 5.6 ppb), O3 stress (79.7 ± 5.4 ppb) and straw treatment (no straw return and straw return). O3 stress significantly decreased root biomass. Straw return significantly increased root biomass under O3 stress at branching and flowering stages. Generally, O3 stress and straw return showed significant effects on the C, N and P concentrations of leaves and soils, and stoichiometric ratios of leaves, stems and microbial biomass. The C, N and P concentrations and stoichiometry of leaves, stems, roots and soils in response to O3 stress and straw return at the branching stage were inconsistent with the changes observed at the flowering and podding stages. The P conversion efficiency showed significant relationship with root P concentration under the combined effects of O3 stress and straw return. Altogether, the present study indicated that C, N and P concentrations of soybean might be more important than stoichiometric ratios as a driver of root defence against O3 stress in the case of straw return.

Ozone episodes during and after the 2018 Chinese National Day holidays in Guangzhou: Implications for the control of precursor VOCs

The impact of reducing industrial emissions of volatile organic compounds (VOCs) on ozone (O₃) pollution is of wide concern particularly in highly industrialized megacities. In this study, O₃, nitrogen oxides (NOx) and VOCs were measured at an urban site in the Pearl River Delta region during the 2018 Chinese National Day Holidays and two after-holiday periods (one with ozone pollution and another without). O₃ pollution occurred throughout the 7-day holidays even industrial emissions of VOCs were passively reduced due to temporary factory shutdowns, and the toluene to benzene ratios dropped from ∼10 during non-holidays to ∼5 during the holidays. Box model (AtChem2-MCM) simulations with the input of observation data revealed that O₃ formation was all VOC-limited, and alkenes had the highest relative incremental reactivity (RIR) during the holiday and non-holiday O₃ episodes while aromatics had the highest RIR during the non-pollution period. Box model also demonstrated that even aromatics decreased proportionally to levels with near-zero contributions of industrial aromatic solvents, O₃ concentrations would only decrease by less than 20% during the holiday and non-holiday O₃ episodes and ozone pollution in the periods could not be eliminated. The results imply that controlling emissions of industrial aromatic solvents might be not enough to eliminate O₃ pollution in the region, and more attention should be paid to anthropogenic reactive alkenes. Isoprene and formaldehyde were among the top 3 species by RIRs in all the three pollution and non-pollution periods, suggesting substantial contribution to O₃ formation from biogenic VOCs.

Spatiotemporal variations of surface ozone and its influencing factors across Tibet: A Geodetector-based study

Reasons regarding surface ozone formation and distribution in remote regions is limited. Tibet is an important remote area on Earth, with various climates and extremely high elevation (average ~ 4000 m), which makes it a good place to study the spatiotemporal distribution of surface ozone and explore the causes. Based on ground monitoring data from 18 stations on Tibet between 2015 and 2019, the annual, seasonal, monthly, and diurnal variations of surface ozone were analyzed. The annual mean values (60.7-72.5 μg/m³) presented an increasing trend during the past five years, with seasonal concentrations of surface ozone higher in spring than in winter. Spatially, both the ground observations and high-resolution remote sensing data indicated that the surface ozone was relatively high in the southwest regions of Tibet, and low in the southeast and northeast areas. Geodetector analysis found that relative humidity (RH), normalized difference vegetation index (NDVI), and solar radiation (SR) were the top three individual factors affecting surface ozone distribution, while NO₂, PM₁₀, and PM_2.5 showed less influence. All influencing factors showed an improvement through the two-factor interaction. The associations of RH∩PM₁₀ (q = 0.77), RH∩NDVI (q = 0.72), and NDVI∩SR (q = 0.73) exhibited a strong impact on surface ozone distribution, suggesting that places with sparse vegetation cover, dry climate and strong SR would usually cause high atmospheric ozone burden. This could also explain why concentrations of surface ozone continue to increase in some remote areas worldwide with ecological deterioration and desertification.

Temporal and spatial variations of air pollution across China from 2015 to 2018

This study investigated concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃, and air quality index (AQI) values across 368 cities in mainland China during 2015-2018. The study further examined relationships of air pollution status with local industrial capacities and vehicle possessions. Strong correlations were found between industrial capacities (coal, pig iron, crude steel and rolled steel) and air pollution levels. Although statistical and significant reductions of PM_2.5, PM₁₀, SO₂, NO₂, CO and AQI values were observed in response to various laws and regulations in industrial sectors, both particle and gaseous pollutants still had annual average concentrations above recommended limits. In order to further reduce air pollution, more efforts can be done to control traffic emissions caused by minicars and heavy trucks, which was revealed after investigating 16 vehicle types. This was also consistent with the apparent air quality improvement during the COVID-19 lockdown period in China in 2020, despite industrial operations being still active at full capacities.

Interannual evolution of elemental carbon-containing particles in winter in the atmosphere of Chengdu, China

As one of the important components of PM_2.5, elemental carbon (EC) particles could quickly mix with other organic or inorganic species after entering the atmosphere, which directly affected its climate and environmental effects and impact on human health. In order to study the mixture and evolution of EC particles in the atmosphere, this study used single particle aerosol mass spectrometry to measure the EC-containing particles in three winters (2016/17, 2018/19 and 2019/20) in Chengdu, one of the most polluted megacities in China. The results showed that the average mass concentrations of PM_2.5 in the three winters were 121 ± 58 μg m^-3, 90 ± 32 μg m^-3 and 79 ± 38 μg m^-3, respectively, and the mass ratios of PM_2.5/PM₁₀ were 0.71, 0.78 and 0.78, respectively. EC-containing particles accounted for 40.7%-54.7% of all particles and could be divided into six categories: EC-dust (EC-D), fresh EC (EC_f), EC-organic carbon (EC-OC), EC-nitrate (EC-N), EC-sulfate (EC-S) and EC-sulfate-nitrate (EC-SN). From winter 2016/17 to 2019/20, the contributions of EC-N and EC-OC particles increased, while the contributions of EC-S and EC-SN particles decreased. Meanwhile, EC-N particles became increasingly important for the formation of heavy pollution. Photochemical and liquid-phase processes dominated the formation of EC-N and EC-S particles, respectively, while the dominant formation mechanism of EC-SN particles changed from photochemical to liquid-phase processes from winter 2016/17 to 2019/20. Total EC and EC-S particles in Chengdu were mainly transported from the east and southeast areas to Chengdu, while EC_f particles mainly derived from local emissions. Compared with the previous two winters, the potential source areas of the EC-containing particles in winter 2019/20 reduced significantly. These findings provide new insight into the atmospheric behavior of urban particles and are important reference for the study of EC particles in other regions in the world, especially in urban areas.

The effects of indoor and outdoor air pollution on the prevalence of adults' respiratory diseases in four Chinese cities: a comparison between 2017-2018 and 1993-1996

Background

Over the past decades, both ambient and household air pollution have changed in several aspects, including the emission sources and the concentrations of pollutants, in many Chinese cities. It is unknown whether these changes are associated with changes in health conditions, especially given changes in other factors due to rapid economic growth.

Methods

Two cross-sectional surveys were conducted in two periods spanning more than twenty years (1993–1996 vs. 2017–2018) in four Chinese cities of Chongqing, Wuhan, Lanzhou, and Guangzhou. Data were collected regarding adults’ respiratory disease, smoking status, education, occupation, and household characteristics. Ambient air pollution data were obtained for each study. We first used logistic regression models to construct the district-specific adjusted disease prevalences. In the second stage, first-difference regression models were employed to examine whether the change in respiratory diseases prevalences was associated with the change in outdoor air pollution and indoor air pollution surrogates.

Results

A total of 7,557 and 9,974 households were participating in Period 1 (1993–1996) and Period 2 (2017–2018), respectively. Compared to Period 1, we found substantial reductions in the ambient air pollution concentrations, and a suggestive improvement in cooking-related indoor air pollution in Period 2. We observed decreases in the district-specific covariate-adjusted prevalences of both asthma and chronic bronchitis among participants, with an average reduction of 3.6% (range: 0.0% to 24.3%). From Period 1 to Period 2, one percent decrease in the proportion of cooking with coal was associated with a 19.0% (95% CI, 0.96–37.04%) decrease in the prevalence of males’ chronic bronchitis and a 1.86% (0.69–3.04%) increase in the prevalence of females’ asthma. Little evidence was observed regarding the potential health benefits associated with the decreases in ambient air pollution levels.

Conclusions

The substantial reduction in household use of coal for cooking might be an important contributor to the decrease in adults’ respiratory disease prevalence from 1993–1996 to 2017–2019 in four Chinese cities. Changes in this indoor air pollution source, along with other risk factors for respiratory diseases, may have masked respiratory health benefits associated with reductions in outdoor air pollution levels.

An investigation into the impact of variations of ambient air pollution and meteorological factors on lung cancer mortality in Yangtze River Delta

Lung cancer (LC) mortality, as one of the top cancer deaths in China, has been associated with increased levels of exposure to ambient air pollutants. In this study, different lag times on weekly basis were applied to study the association of air pollutants (PM2.5, PM10, and NO2) and LC mortality in Ningbo, and in subpopulations at different age groups and genders. Furthermore, seasonal variations of pollutant concentrations and meteorological variables (temperature, relative humidity, and wind speed) were analysed. A generalised additive model (GAM) using Poisson regression was employed to estimate the effect of single pollutant model on LC mortality in Yangtze River Delta using Ningbo as a case study. It was reported that there were statistically significant relationships between lung cancer mortality and air pollutants. Increases of 6.2% (95% confidence interval [CI]: 0.2% to 12.6%) and 4.3% (95% CI: 0.1% to 8.5%) weekly total LC mortality with a 3-week lag time were linked to each 10 μg/m³ increase of weekly average PM_2.5 and PM₁₀ respectively. The association of air pollutants (PM_2.5, PM₁₀ and NO₂) and LC mortality with a 3-week lag time was also found statistically significant during periods of low temperature (T < 18 °C), low relative humidity (H < 73.7%) and low wind speed (u < 2.8 m/s), respectively. The female population was found to be more susceptible to the exposure to air pollution than the male population. In addition, the population with an age of 50 years or above was shown to be more sensitive to ambient air pollutant. These outcomes indicated that increased risk of lung cancer mortality was evidently linked to exposure to ambient air pollutant on a weekly basis. The impact of weekly variation on the LC mortality and air pollutant levels should be considered in air pollution-related health burden analysis.

Analysis of Ozone Pollution Characteristics and Influencing Factors in Northeast Economic Cooperation Region, China

The increase in tropospheric ozone (O3) concentration has become one of the factors restricting urban development. This paper selected the important economic cooperation areas in Northeast China as the research object and collected the hourly monitoring data of pollutants and meteorological data in 11 cities from 1 January 2015 to 31 December 2019. The temporal and spatial variation trend of O3 concentration and the effects of meteorological factors and other pollutants, including CO (carbon monoxide), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and PM2.5 and PM10 (PM particles with aerodynamic diameters less than 2.5 μm and 10 μm) on ozone concentration were analyzed. At the same time, the variation period of O3 concentration was further analyzed by Morlet wavelet analysis. The results showed that the O3 pollution in the study area had a significant spatial correlation. The spatial distribution showed that the O3 concentration was relatively high in the south and low in the northeast. Seasonally, the O3 concentration was the highest in spring, followed by summer, and the lowest in winter. The diurnal variation of O3 concentration presented a “single peak” pattern. O3 concentration had a significant positive correlation with temperature, sunshine duration, and wind speed and a significant anticorrelation with CO, NO2, SO2, and PM2.5 concentration. Under the time scale of a = 9, 23, O3 had significant periodic fluctuation, which was similar to those of wind speed and temperature.

Ambient ozone pollution at a coal chemical industry city in the border of Loess Plateau and Mu Us Desert: characteristics, sensitivity analysis and control strategies

In this study, ambient ozone (O₃) pollution characteristics and sensitivity analysis were carried out in Yulin, a city in the central area of the Loess Plateau during 2017 to 2019 summer. O₃ concentrations increased for 2017 to 2019. Correlation and statistics analysis indicated high temperature (T > 25 °C, low relative humidity (RH < 60%), and low wind speed (WS < 3 m/s) were favorable for O₃ formation and accumulation, and the O₃ pollution days (MDA8 O₃ > 160 µg/m³) were predominantly observed when the wind was traveling from the easterly and southerly. O₃ concentration in urban area of Yulin was higher than that in background. The pollution air masses from Fenwei Plain increase the level and duration of O₃ pollution. In order to clarify the formation mechanism and source of O₃, online measurements of volatile organic compounds (VOCs) were conducted from 7 July to 10 August in 2019. The average of VOCs concentration was 26 ± 12 ppbv, and large amounts of alkenes followed by aromatics, characteristic pollutants of the coal chemical industry, were detected in the ambient air. To further measure the sensitivity, the observation-based model (OBM) simulation was conducted. Empirical Kinetic Modeling Approach (EKMA) plot and relative incremental reactivity (RIR) value indicated Yulin located on VOCs-limited regime. That implied a slight decrease of NO_x may increase O₃ concentration. When the emission reduction ratio of anthropogenic VOCs/NO_x higher than 1:1, the O₃ will decrease. O₃ control strategies analysis shows that the O₃ targets of 5% and 10% O₃ concentration reductions are achievable through precursor control, but more effort is needed to reach the 30% and 40% reduction control targets.

Ambient PM2.5 and Related Health Impacts of Spontaneous Combustion of Coal and Coal Gangue

Coal and coal gangue spontaneous combustion (CGSC) occurs globally, causing significant environmental pollution. However, its emissions are poorly quantified and are overlooked in global or regional air pollutant emission inventories in previous studies, resulting in the underestimation of its impacts on climate, environment, and public health. This study quantified the emissions of various air pollutants originating from CGSC in Wuhai, a city in China, investigated emission characteristics, and estimated the contribution of CGSC emissions to fine particulate matter (PM_2.5) air pollution and related health impacts on a regional scale. The results revealed that the CGSC-related PM_2.5 emissions were approximately 4643 t a^-1 (95% confidence interval (95% CI): 721; 10447), accounting for 26.3% of the total PM_2.5 emissions. Alkanes, alkenes, and aromatics accounted for 69.4, 17.9, and 2.9%, respectively, of the total emissions of volatile organic compounds (VOCs). Due to CGSC emissions, the ambient PM_2.5 concentration in Wuhai increased by 5.7 μg m^-3 on average, while the nitrate concentration decreased. The number of premature deaths caused by exposure to ambient PM_2.5 associated with CGSC reached 381 (95% CI: 290; 452) in Wuhai and surrounding cities in 2017. Urgent control strategies and engineering techniques are needed to mitigate CGSC to protect public health.

Estimating Spatiotemporal Variation in Ambient Ozone Exposure during 2013-2017 Using a Data-Fusion Model

Since 2013, clean-air actions in China have reduced ambient concentrations of PM_2.5. However, recent studies suggest that ground surface O₃ concentrations increased over the same period. To understand the shift in air pollutants and to comprehensively evaluate their impacts on health, a spatiotemporal model for O₃ is required for exposure assessment. This study presents a data-fusion algorithm for O₃ estimation that combines in situ observations, satellite remote sensing measurements, and model results from the community multiscale air quality model. Performance of the algorithm for O₃ estimation was evaluated by five-fold cross-validation. The estimates are highly correlated with the in situ observations of the maximum daily 8 h averaged O₃ (R² = 0.70). The mean modeling error (measured using the root-mean-squared error) is 26 μg/m³, which accounts for 29% of the mean level. We also found that satellite O₃ played a key role to improve model performance, particularly during warm months. The estimates were further used to illustrate spatiotemporal variation in O₃ during 2013-2017 for the whole country. In contrast to the reduced trend of PM_2.5, we found that the population-weighted O₃ mean increased from 86 μg/m³ in 2013 to 95 μg/m³ in 2017, with a rate of 2.07 (95% CI: 1.65, 2.48) μg/m³ per year at the national level. This increased trend in O₃ suggests that it is becoming an important contributor to the burden of diseases attributable to air pollutants in China. The developed method and the results generated from this study can be used to support future health-related studies in China.

Persistent ozone pollution episodes in North China exacerbated by regional transport

Summertime ozone (O₃) concentrations over China continue to increase although the governmental Clear Air Actions have been carried out since 2013. The worst O₃ pollution is confronted over North China Plain. Ozone polluted days (with observed regionally-averaged maximum daily 8-h average (MDA8) O₃ concentrations exceeding 80 ppbv) in May-July in North China increased from 35 days in year 2014 to 56 days in year 2018, and persistent O₃ pollution episodes that lasted for 5 days or longer (OPEs5) contributed 14.3% and 66.1% to those O₃ polluted days in 2014 and 2018, respectively. Model simulations suggest that O₃ transport from central eastern China (including Shandong, Henan, Jiangsu and Anhui Provinces) contributes 36% of the enhanced O₃ concentrations in North China during OPEs5 relative to the seasonal mean. We find that emission control of volatile organic compounds in central eastern China is most effective to alleviate intensity of OPEs5 in North China.

Modeling Ozone Source Apportionment and Performing Sensitivity Analysis in Summer on the North China Plain

In recent years, air quality issues due to fine particulate matter have been sufficiently treated. However, ozone (O3) has now become the primary pollutant in summer on the North China Plain (NCP). In this study, a three-dimensional chemical transport model (the Nested Air Quality Prediction Model System, NAQPMS) coupled with an online source apportionment module was applied to investigate the sources of O3 pollution over the NCP. Generally, the NAQPMS adequately captured the observed spatiotemporal features of O3 during the period of July 1st to August 31st in 2017 on the NCP. The results of the source apportionment indicated that the contributions of local emissions and transport from the NCP accounted for the largest proportion of O3, with magnitudes of 25% and 39%, respectively. Compared with those in the average monthly results, the local contribution and regional transport during O3 episodes on the NCP increased by 7% and 10%, respectively. Based on sensitivity tests, two thresholds of the sensitivity indicator P(H2O2)/P(HNO3) were detected, at 0.08 and 0.2. Ozone formation in the urban sites of Beijing, Tianjin, and the southern part of Hebei Province was controlled by VOCs, while the other sites were mainly controlled by NOX. Biogenic emissions contributed approximately 18% to O3 formation in July in the southwestern part of Hebei Province.

Using a distributed air sensor network to investigate the spatiotemporal patterns of PM2.5 concentrations

Spatiotemporal variations in PM_2.5 are a key factor affecting personal pollution exposure levels in urban areas. However, fixed-site monitoring stations are so sparsely distributed that they hardly capture the dynamic and fine-scale variations in PM_2.5 in urban areas with complex geographical features and urban forms. Recently, a distributed air sensor network (DASN) was deployed in Dezhou city, China, to monitor fine-scale air pollution information and obtain deep insight into variations in PM_2.5. Based on the data collected by the DASN, this paper investigated the spatiotemporal patterns of PM_2.5 using the time-series clustering method. The results demonstrated that there were four stages of PM_2.5 daily variations, i.e., accumulation, continuous pollution, dispersion, and cleaning. Generally, the stage of dispersion occurred more rapidly than the stage of accumulation, and PM_2.5 accumulated easily in warm and humid weather with low wind speeds. However, the stage of dispersion was affected mainly by high wind speeds and precipitation. Additionally, the results suggested that four variation stages did not strictly correspond to seasonal divisions. The spatial distributions of PM_2.5 revealed that the main pollution source was located in a southeastern industrial park, which exhibited a significant impact throughout the four stages. Considering both the temporal and spatial characteristics of PM_2.5, this study successfully identified pollution hotspots and confirmed the effect of industrial parks. The study demonstrates that the DASN has high prospective applicability for assessing the fine-scale spatial distribution of PM_2.5, and the time-series clustering method can also assist environmental researchers in further exploring the spatiotemporal characteristics of urban air pollution.

The spatiotemporal characteristics of the air pollutants in China from 2015 to 2019

China’s rapid industrialization and urbanization have led to poor air quality, and air pollution has caused great concern among the Chinese public. Most analyses of air pollution trends in China are based on model simulations or satellite data. Studies using field observation data and focusing on the latest data from environmental monitoring stations covering the whole country to assess the latest trends of different pollutants in different regions are relatively rare. The State Council of China promulgated the toughest-ever Air Pollution Prevention and Control Action Plan (Action Plan) in 2013. This led to a major improvement in air quality. We use the hourly Air Quality Index (AQI) and mass concentrations of PM_2.5, PM₁₀, CO, NO₂, O₃, and SO₂ in 362 cities from 2015 to 2019, obtained from the Ministry of Ecology and Environment, to study their temporal and spatial changes and assess the effectiveness of the policy on the atmospheric environment since its promulgation and implementation. We found that the national and regional air quality in China continues to improve, with PM_2.5, PM₁₀, AQI, CO, and SO₂ exhibiting negative trends. However, O₃ and NO₂ pollution is an urgent problem that needs to be solved and the current control strategy for PM_2.5 will only partially reduce the PM_2.5 pollution in the western region. Although the implementation of "Action Plan" measures has effectively improved air quality, China’s air pollution is still serious and far from the WHO standard. Implementing measures for continuous and effective emissions control is still a top priority.

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

Ground-level ozone pollution has negative impacts on human health and vegetation and has increased rapidly across China. Various factors are implicated in the formation of ozone (e.g., meteorological factors, anthropogenic emissions), but their relative individual impact and the impact of interactions between these factors remains unclear. This study quantified the influence of specific meteorological conditions and anthropogenic precursor emissions and their interactions on ozone concentrations in Chinese cities using the geographic detector model (GeoDetector). Results revealed that the impacts of meteorological and anthropogenic factors and their interactions on ozone concentrations varied significantly at different spatial and temporal scales. Temperature was the dominant driver at the annual time scale, explaining 40% (q = 0.4) of the ground-level ozone concentration. Anthropogenic precursors and meteorological conditions had comparable effects on ozone concentrations in summer and winter in northern China. Interactions between all the factors can enhance effects. The interaction between meteorological factors and anthropogenic precursors had the strongest impact in summer. The results can be used to enhance our understanding of ozone pollution, to improve ozone prediction models, and to formulate pollution control measures.

No Evidence for a Significant Impact of Heterogeneous Chemistry on Radical Concentrations in the North China Plain in Summer 2014

The oxidation of nitric oxide to nitrogen dioxide by hydroperoxy (HO₂) and organic peroxy radicals (RO₂) is responsible for the chemical net ozone production in the troposphere and for the regeneration of hydroxyl radicals, the most important oxidant in the atmosphere. In Summer 2014, a field campaign was conducted in the North China Plain, where increasingly severe ozone pollution has been experienced in the last years. Chemical conditions in the campaign were representative for this area. Radical and trace gas concentrations were measured, allowing for calculating the turnover rates of gas-phase radical reactions. Therefore, the importance of heterogeneous HO₂ uptake on aerosol could be experimentally determined. HO₂ uptake could have suppressed ozone formation at that time because of the competition with gas-phase reactions that produce ozone. The successful reduction of the aerosol load in the North China Plain in the last years could have led to a significant decrease of HO₂ loss on particles, so that ozone-forming reactions could have gained importance in the last years. However, the analysis of the measured radical budget in this campaign shows that HO₂ aerosol uptake did not impact radical chemistry for chemical conditions in 2014. Therefore, reduced HO₂ uptake on aerosol since then is likely not the reason for the increasing number of ozone pollution events in the North China Plain, contradicting conclusions made from model calculations reported in the literature.

The Functional Spatio-Temporal Statistical Model with Application to O3 Pollution in Beijing, China

In recent years, with rapid industrialization and massive energy consumption, ground-level ozone (O3) has become one of the most severe air pollutants. In this paper, we propose a functional spatio-temporal statistical model to analyze air quality data. Firstly, since the pollutant data from the monitoring network usually have a strong spatial and temporal correlation, the spatio-temporal statistical model is a reasonable method to reveal spatial correlation structure and temporal dynamic mechanism in data. Secondly, effects from the covariates are introduced to explore the formation mechanism of ozone pollution. Thirdly, considering the obvious diurnal pattern of ozone data, we explore the diurnal cycle of O3 pollution using the functional data analysis approach. The spatio-temporal model shows great applicational potential by comparison with other models. With application to O3 pollution data of 36 stations in Beijing, China, we give explanations of the covariate effects on ozone pollution, such as other pollutants and meteorological variables, and meanwhile we discuss the diurnal cycle of ozone pollution.

Spatiotemporal distribution of ground-level ozone in China at a city level

In recent years, ozone (O3) pollution in China has shown a worsening trend. Due to the vast territory of China, O3 pollution is a widespread and complex problem. It is vital to understand the current spatiotemporal distribution of O3 pollution in China. In this study, we collected hourly data on O3 concentrations in 338 cities from January 1, 2016, to February 28, 2019, to analyze O3 pollution in China from a spatiotemporal perspective. The spatial analysis showed that the O3 concentrations exceeded the limit in seven geographical regions of China to some extent, with more serious pollution in North, East, and Central China. The O3 concentrations in the eastern areas were usually higher than those in the western areas. The temporal analysis showed seasonal variations in O3 concentration, with the highest O3 concentration in the summer and the lowest in the winter. The weekend effect, which occurs in other countries (such as the USA), was found only in some cities in China. We also found that the highest O3 concentration usually occurred in the afternoon and the lowest was in the early morning. The comprehensive analysis in this paper could improve our understanding of the severity of O3 pollution in China.

Summertime ozone pollution in the Yangtze River Delta of eastern China during 2013-2017: Synoptic impacts and source apportionment

Severe ozone (O₃) pollution in China has magnified global concerns over the past years. Exploring the synoptic impacts and quantifying the source contributions are important for mitigating O₃ pollution. This study focuses on the summertime O₃ pollution over the Yangtze River Delta (YRD) in eastern China. We identify six predominant synoptic weather patterns (SWPs) over the YRD during 2013-2017 using the self-organising map (SOM) approach. We conduct O₃ source attribution based on ozone source apportionment technology (OSAT) in a regional transport model. Surface O₃ pollution is found to be sensitive to the predominant SWPs, including four O₃-polluted types (northeasterly, northerly and southwesterly and anticyclone) and two O₃-clean types (cyclone and the Meiyu front). The integrated influences of local chemistry and regional transport are important in O₃ pollution under different SWPs. Daily maximum 8-h average (MDA8) O₃ holds strong negative and positive correlations with relative humidity and sunshine duration, respectively. Among the six SWPs, the concentration and exceedance of MDA8 O₃ reach their maxima under the northerly type on a regional average. Higher O₃ levels, particularly under the northerly and northeasterly types, are primarily related to regional transport on various spatial scales. Local production accounts for the largest proportion of O₃ sources under the anticyclone type. Under the southwesterly type, favourable weather conditions superimposed on regional transport lead to severe O₃ pollution in coastal cities. The impact of super-regional transport is most pronounced along the eastern coast under the cyclone type. Source category analysis shows that transportation and industrial emissions play a prime role in surface O₃ formation. This study illustrates the imperative implementation of joint emission control over eastern China to reduce O₃ pollution.

Characteristics of Ground-Level Ozone from 2015 to 2018 in BTH Area, China

With the ground-level ozone pollution problem increasingly prominent in recent years in China, it is particularly important in basic researches on ozone contamination characteristics. In this study, 13 cities in Beijing-Tianjin-Hebei (BTH) area were examined to determine the characteristics of surface ozone (O3) from 2015 to 2018. Due to the photochemical oxidation of ozone precursors (such as nitrogen oxides and carbon monoxide) along with the presence of sunlight and characteristics of local emission sources, the O3 and oxidant (OX) concentrations showed obvious seasonal variation and daily variation. It implicated that the O3 concentrations reached the maximum during summer. The concentrations of O3 were higher at daytime than those measured at nighttime. The ozone weekend effect was estimated by the difference and deviation, which exhibited that the difference between weekday and weekend were related to the concentrations of ozone precursors and PM, vehicle emissions, and solar radiation. Moreover, the O3 concentrations decreased with the increase of other air pollutants by correlation analysis. The ozone pollution was easily formed at light and moderate polluted periods when compared to other air quality levels.

Characteristics of Surface Ozone in Five Provincial Capital Cities of China during 2014–2015

Ozone (O3) pollution has become an increasing concern in China since elevated surface O3 concentrations were observed in recent years. In this study, five provincial cities (Beijing, Shanghai, Guangzhou, Xi’an, and Hefei) located in different regions of China were selected to study the spatiotemporal variations and affecting factors of O3 concentrations during 2014–2015. Beijing, Shanghai, and Guangzhou had suffered more severe O3 pollution, yet Beijing had the highest number of days that exceeded the Chinese MDA8 (maximum daily 8 h average) standard of 160 µg m−3. MDA8 O3 exhibited different seasonal patterns among the five cities. In Beijing and Xi’an, MDA8 O3 showed the highest in summer and lowest in winter. Guangzhou also had the highest O3 concentration in summer, but had similar levels in other three seasons. The O3 levels were similarly high in Shanghai during spring, summer, and autumn, while in Hefei, O3 concentration peaked in autumn. No significant difference between weekend and weekday O3 levels was observed in all the five cities. The diurnal cycle reached a maximum in the afternoon and a minimum in the early morning, which was consistent in the five cities. Correlation analyses showed that the associations between O3 and the other five criteria air pollutants, as well as meteorological parameters, were substantially different among the five cities. Air mass cluster analyses during episodic days revealed that the short-distance transport of O3 and its precursors had a greater impact for high O3 pollution in the five cities. Overall, our results demonstrate that O3 pollution exhibited great divergence among different regions and thus region-oriented control measures are suggested to reduce O3 pollution in China.

Geographical distribution of ozone seasonality over China

Up to now, a nation-wide scale study of surface ozone (O₃) concentrations in China was limited due to scarce observation. Thanks to the establishment of national air quality monitoring network in 2013, surface O₃ data from 1402 stations during 2014-2017 were collected to investigate O₃ seasonality. Our analysis reveals that the variations of monthly O₃ averaged from daily mean concentration during a year show different temporal profiles depending on latitude. A unimodal structure (UMS) is generally found for latitudes over 35°N, whereas a bimodal structure (BMS) is in most of the cases identified south of 35°N. The peak of UMS is found in the period of May to July, whereas the first and second peaks of BMS are found from April to June, and from July to October, respectively. In addition, the seasonality of O₃ presents a strong dependence on pseudo-equivalent potential temperature and monsoonal clouds. The onset and retreat of warm and wet air are correlated to the summer minimum in BMS cases and to the sharp decrease of UMS in July. As far as the relationships between O₃ and carbon monoxide are concerned, the effects of clean maritime air masses on the summer trough of O₃ are not significant for inland sites. Overall, summer monsoon bringing warm and moist air and subsequent clouds leads to the suppression of photochemical production, thereby contributing directly to the geographical distribution of O₃ seasonality.

Spatial and temporal variations of air quality and six air pollutants in China during 2015-2017

Air pollution has aroused significant public concern in China, therefore, long-term air-quality data with high temporal and spatial resolution are needed to understand the variations of air pollution in China. However, the yearly variations with high spatial resolution of air quality and six air pollutants are still unknown for China until now. Therefore, in this paper, we analyze the spatial and temporal variations of air quality and six air pollutants in 366 cities across mainland China during 2015–2017 for the first time to the best of our knowledge. The results indicate that the annual mean mass concentrations of PM2.5, PM10, SO₂, and CO all decreased year by year during 2015–2017. However, the annual mean NO₂ concentrations were almost unchanged, while the annual mean O₃ concentrations increased year by year. Anthropogenic factors were mainly responsible for the variations of air quality. Further analysis suggested that PM2.5 and PM10 were the main factors influencing air quality, while NO₂ played an important role in the formation of PM2.5 and O₃. These findings can provide a theoretical basis for the formulation of future air-pollution control policy in China.

A temperature indicator for heavy air pollution risks (TIP)

This study presents a temperature indicator for heavy air pollution risks (TIP). This TIP indicator is a temperature threshold, at which the concentrations of air pollutants and air pollution indices easily reach their maxima. A connotation discussion ascertains that TIP is intrinsically associated with the atmospheric structure and static stability in the planetary boundary layer, especially during stagnant weather and moderately cold temperatures. Thus, TIP offers a simple measure of meteorological conditions that reflect the boundary layer static characteristics. It therefore provides a simple measure of air pollution potential, and can be used to quantify the potential air pollution severity for a given pollution emission level. From the data collected in China, TIP increases gradually from north to south and decreases slightly from east to west, which essentially indicates a function of latitude and altitude. A simple regressive function is built for TIP, and the resulting TIP index further confirms that it is indicative of the potential heavy air pollution events across the country. Being an easy-to-obtain and simple-to-use meteorological parameter, TIP can be used for air pollution potential assessment and prediction, as well as pollution prevention and control applications.

The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

Overview on the spatial-temporal characteristics of the ozone formation regime in China

Ozone (O3), a main component in photochemical smog, is a secondary pollutant formed through complex photochemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs). In the past few decades, with the rapid economic development, industrialization and urbanization, the mixing ratio of O3 has increased substantially in China. O3 non-attainment days have been frequently observed. Despite great efforts made in the past few years, it is still difficult to alleviate O3 pollution in China, due to its non-linear relationship with the precursors. In view of the severe situation in China, this study presents a comprehensive review on the spatial-temporal variations of the relationship between O3 and its precursors (i.e. O3 formation regime), built upon the previous reviews of the spatial-temporal variations of O3 and its precursor levels. Valuable findings from previous studies are laid out for a better understanding of O3 pollution, followed by implications for the control of O3 pollution. This literature review indicates that O3 formation in most areas of the North China Plain (NCP), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions is in a VOC-limited regime during the high-O3 seasons due to dramatic emissions from human activities in cities. Outside these metropolitan areas, a NOx-limited regime dominates rural/remote areas. From summer to winter, the O3 formation regime over China shows a tendency to shift to a VOC-limited regime. Furthermore, O3 formation in China shifted toward increasing sensitivity to VOC emissions before the 12th Five-Year-Plan. However, after the 12th Five-Year-Plan, successful reduction of NOx slowed down this trend. Further effective control of VOCs is expected to achieve sustained O3 attainment in the future. To timely solve the current O3 pollution problem, precise control of O3 precursors is proposed, together with the joint prevention and control of regional air pollution.

Air pollution reduction in China: Recent success but great challenge for the future

China's rapid economic growth has caused severe air pollution, raising serious concerns about the growing evidence of its negative health, environmental, and economic impacts. Consequently, the Chinese government has implemented a number of policies and measures to reduce air pollution. Relying on published information over the last three decades in China, we analyzed trends in air pollutant emissions (SO₂ and NO_x) and concentrations of particulate matter (PM) and ozone (O₃). During the past decade, SO₂ and NO_x emissions had declined throughout China and concentrations of PM_2.5 and PM₁₀ had considerably decreased in most cities, but average reported 90th MDA8 O₃, M7, and AOT40 O₃ for 31 capital cities showed an increasing trend between 2013 and 2017. Despite progress in air pollution reduction and an increasing number of "clear sky" days, PM concentrations throughout China remain higher than the World Health Organization guidelines, and urban smog and haze remain a major threat to human health and the environment. Thus far, significant emission reductions have occurred largely through robust administrative power, especially when emission reductions were tied to the performance evaluations and promotion of government officials. Similar to most already-industrialized nations, China is now shifting away from SO₂-dominated to NO_x- and O₃-dominated air pollution. Existing technologies and improved operations of existing control equipment appear unlikely to achieve sufficient reductions in NO_x and O₃ pollution. Considering the complex relationship between O₃, NO_x, VOCs, weather, and socio-economic changes in China, it is necessary to increase research on impacts of increasing ozone on plants and to adopt novel technologies and implemented to further reduce air pollution to levels that will protect human health and the environment.

Analysis of the Spatial–Temporal Variation of the Surface Ozone Concentration and Its Associated Meteorological Factors in Changchun

Ozone (O3) pollution has become one of the most challenging problems in China, and high O3 concentrations have been a major air quality issue in Changchun. Based on continuous observation data of surface ozone concentrations from ten automatic air monitoring stations and meteorological data from the meteorological bureau in Changchun, the temporal and spatial variations of the O3 concentration and its relationships with meteorological factors were analyzed by correlation analysis during the period of 2013–2017. The results showed the following: A single apex model of the annual mean O3 concentrations of the daily maximum 8 h average (MDA8) was found from the data for 2013 to 2017 in Changchun, with the highest MDA8 O3 concentrations in 2015 and a slight decline from then until 2017. The O3 concentrations in the suburban areas and the south of Changchun were higher than those downtown and north of the city. The seasonal variation of O3 concentrations was obvious, following the order summer > spring > autumn > winter, which was similar to the results of neighboring cities and provinces in Changchun. The days on which O3 concentrations exceeded the standard were concentrated in summer and spring, and the total number of ozone excess days was 91 days; the maximum number of ozone excess days was in 2015. The O3 concentration exceeded the standard in Changchun mainly in March–August, and its monthly mean value curve showed a bimodal type in which the highest values appeared in May and July, while the lowest values appeared in December. The diurnal pattern of ozone showed a single peak mode, and the peak value usually appeared at 14:00–16:00 while the minimum value appeared at 07:00–08:00. O3 concentrations in Changchun and the six selected pollutants CO, NO, NO2, NOx, PM10, and PM2.5 were negatively correlated. Higher temperature is a necessary synoptic condition for ozone pollution in Changchun: when the temperature rose, O3 concentrations increased significantly; further, O3 concentrations were negatively correlated with relative humidity and atmospheric pressure and were positively correlated with temperature and solar radiation. The O3 concentrations were highest when the wind scale approached 14~20 km/h and the wind direction was S. Combined with the research results in the surrounding areas of Changchun, it is indicated that there may be an ozone contribution from south of Changchun through long-range pollution transport and tropospheric subsidence.

Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China

Tremendous efforts have been made to reduce the severe air pollution in China since 2013. However, the annual and peak fine particulate matter (PM_2.5) concentrations during severe events in winter did not always reduce as expected. This is partially due to the inter-annual variation of meteorology, which affects the emission, transport, transformation, and deposition processes of air pollutants. In this study, the responses of PM_2.5 and ozone (O₃) concentrations to changes in emission and meteorology from 2013 to 2015 were investigated based on ambient measurements and the Community Multi-Scale Air Quality (CMAQ) model simulations with anthropogenic emissions. It is found that emission reductions in 2014 and 2015 effectively reduced PM_2.5 concentrations by 23.9 and 43.5 μg/m³, respectively, but was partially counteracted by unfavorable meteorology. The negative effects from unfavorable meteorology were significant in extreme pollution events. For example, in December 2015, unfavorable meteorology caused a great increase (90 μg/m³) of PM_2.5 in Beijing. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of O₃-8 h daily concentrations in the summertime in 2014 and 2015 in comparison of 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. In addition, reduction of nitrogen oxides (NOx) emissions in areas with negative NOx-O₃ sensitivity could lead to an increase of O₃ formation when the reduction of volatile organic compounds (VOCs) was not sufficient. This unintended enhanced O₃ formation could also lead to higher O₃ in downwind areas. This study emphasizes the role of meteorology in pollution control, validates the effectiveness of PM_2.5 control measures in China, and highlights the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O₃ and PM_2.5 for higher air quality.

Spatio-Temporal Characteristics of Tropospheric Ozone and Its Precursors in Guangxi, South China

The temporal and spatial distributions of tropospheric ozone and its precursors (NO2, CO, HCHO) are analyzed over Guangxi (GX) in South China. We used tropospheric column ozone (TCO) from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite (OMI/MLS), NO2 and HCHO from OMI and CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument in the period 2005–2016. The TCO shows strong seasonality, with the highest value in spring and the lowest value observed in the monsoon season. The seasonal variation of HCHO is similar to that of TCO, while NO2 and CO show slightly different patterns with higher values in spring and winter compared to lower values in autumn and summer. The surface ozone, NO2 and CO observed by national air quality monitoring network sites are also compared with satellite-observed TCO, NO2 and CO, showing good agreement for NO2 and CO but a different seasonal pattern for ozone. Unlike TCO, surface ozone has the highest value in autumn and the lowest value in winter. To reveal the difference, the vertical profiles of ozone and CO from the measurement of ozone and water vapor by airbus in-service aircraft (MOZAIC) observations over South China are also examined. The seasonal averaged vertical profiles of ozone and CO show obvious enhancements at 2–6 km altitudes in spring. Furthermore, we investigate the dependence of TCO and surface ozone on meteorology and transport in detail along with the ECMWF reanalysis data, Tropical Rainfall Measuring Mission (TRMM) 3BV42 dataset, OMI ultraviolet index (UV index) dataset, MODIS Fire Radiative Power (FRP) and back trajectory. Our results show that the wind pattern at 800 hPa plays a significant role in determining the seasonality of TCO over GX, especially for the highest value in spring. Trajectory analysis, combined with MODIS FRP suggests that the air masses that passed through the biomass burning (BB) region of Southeast Asia (SEA) induced the enhancement of TCO and CO in the upper-middle troposphere in spring. However, the seasonal cycle of surface ozone is associated with wind patterns at 950 hPa, and the contribution of the photochemical effect is offset by the strong summer monsoon, which results in the maximum surface ozone concentration in post-monsoon September. The variations in the meteorological conditions at different levels and the influence of transport from SEA can account for the vertical distribution of ozone and CO. We conclude that the seasonal distribution of TCO results from the combined impact of meteorology and long-term transport.

Enhanced near-surface ozone under heatwave conditions in a Mediterranean island

Near-surface ozone is enhanced under particular chemical reactions and physical processes. This study showed the seasonal variation of near-surface ozone in Nicosia, Cyprus and focused in summers when the highest ozone levels were noted using a seven year hourly dataset from 2007 to 2014. The originality of this study is that it examines how ozone levels changed under heatwave conditions (defined as 4 consecutive days with daily maximum temperature over 39 °C) with emphasis on specific air quality and meteorological parameters with respect to non-heatwave summer conditions. The influencing parameters had a medium-strong positive correlation of ozone with temperature, UVA and UVB at daytime which increased by about 35% under heatwave conditions. The analysis of the wind pattern showed a small decrease of wind speed during heatwaves leading to stagnant weather conditions, but also revealed a steady diurnal cycle of wind speed reaching a peak at noon, when the highest ozone levels were noted. The negative correlation of NOx budget with ozone was further increased under heatwave conditions leading to steeper lows of ozone in the morning. In summary, this research encourages further analysis into the persistent weather conditions prevalent during HWs stimulating ozone formation for higher temperatures.

Radiative and heterogeneous chemical effects of aerosols on ozone and inorganic aerosols over East Asia

Currently, many challenges are faced in simulating ozone(O₃), sulfate(SO₄^2-), and nitrate(NO₃^-) concentrations over East Asia, particularly the overestimation of surface O₃ and NO₃^- concentrations and underestimation of the SO₄^2- concentration during haze episodes. In this study, we examined the radiative and heterogeneous chemical effects of aerosols by incorporating recently reported mechanisms, including self-amplifying SO₄^2- formation, dinitrogen pentoxide (N₂O₅) hydrolysis, and a heterogeneous reaction converting gaseous nitric acid (HNO₃) to nitric oxide (NO_x), into a Nested Air Quality Prediction Modeling System. Uptakes by aerosols can be computed through a simple parameterization that is dependent on the aerosol core and shell species, shell thickness, and amount of aerosol liquid water. In this study, a 1-year simulation was conducted for 2013. The updated model successfully reproduced the seasonal and daily observations of O₃, fine particulate matter, SO₄^2-, and NO₃^- concentrations in East Asia. Our results revealed that heterogeneous reactions reduced more surface O₃ concentrations (10-20 ppbv) in the polluted regions of East China than did perturbations in photolysis frequencies from aerosols, effectively again improving the comparison between simulations and observations. Oxidation of SO₂ by NO₂ on wet aerosols significantly enhanced SO₄^2- formation, with sulfate covering approximately ~30-60% of total sulfate concentrations in North China Plain during haze days in winter. The uptake of reactive nitrogen species on aerosols effectively reduced NO₃^- concentrations and successfully balanced the NO_x/HNO₃ chemistry in the models. We recommended that larger reductions of gaseous precursors should be considered in China to achieve the national air quality objective. The results show that surface O₃ concentrations over East China will increase if the emission of aerosols is reduced without corresponding reductions in O₃ precursors.

Temporal and Spatial Variation in, and Population Exposure to, Summertime Ground-Level Ozone in Beijing

Ground-level ozone pollution in Beijing has been causing concern among the public due to the risks posed to human health. This study analyzed the temporal and spatial distribution of, and investigated population exposure to, ground-level ozone. We analyzed hourly ground-level ozone data from 35 ambient air quality monitoring sites, including urban, suburban, background, and traffic monitoring sites, during the summer in Beijing from 2014 to 2017. The results showed that the four-year mean ozone concentrations for urban, suburban, background, and traffic monitoring sites were 95.1, 99.8, 95.9, and 74.2 μg/m³, respectively. A total of 44, 43, 45, and 43 days exceeded the Chinese National Ambient Air Quality Standards (NAAQS) threshold for ground-level ozone in 2014, 2015, 2016, and 2017, respectively. The mean ozone concentration was higher in suburban sites than in urban sites, and the traffic monitoring sites had the lowest concentration. The diurnal variation in ground-level ozone concentration at the four types of monitoring sites displayed a single-peak curve. The peak and valley values occurred at 3:00-4:00 p.m. and 7:00 a.m., respectively. Spatially, ground-level ozone concentrations decreased in gradient from the north to the south. Population exposure levels were calculated based on ground-level ozone concentrations and population data. Approximately 50.38%, 44.85%, and 48.49% of the total population of Beijing were exposed to ground-level ozone concentrations exceeding the Chinese NAAQS threshold in 2014, 2015, and 2016, respectively.