Average O3 Concentrations Research Articles

Impacts of Changes in Land Use and Land Cover Between 2001 and 2018 on Summertime O3 Formation in North China Plain and Surrounding Areas–A Case Study

AbstractChanges in land use and land cover (LULC) influence meteorological fields and biogenic emissions, further affecting the atmospheric chemistry and air quality. Combining the satellite measurements and WRF‐Chem model simulations, we evaluate the impacts of the LULC change between 2001 and 2018 on the summertime ozone (O3) formation in North China Plain and surrounding areas (NCPs). Satellite measurements have revealed that from Taihang to Yanshan Mountain, the fraction of broadleaf and needle forest coverage has increased by 5%–20% and the urban area has increased by up to 25% in the NCP. Additionally, the vegetation density has increased significantly in the NCPs except for urban areas. The LULC change generally enhances biogenic volatile compounds emissions in the NCPs, particularly over Taihang and Yanshan mountain, but the O3 variation is divergent. The maximum daily 8‐ihr average (MDA8) O3 concentrations are reduced by 1%–7% over Taihang and Yanshan Mountain because the raised vegetation density increases O3 dry deposition velocity to accelerate the O3 loss. The raised vegetation density enhances the evapotranspiration to decrease the near‐surface temperature by 0.1°C–1.5°C, which also generates a divergence in the low‐level atmosphere in the NCPs, causing secondary northerly or easterly winds in the NCP. The O3 enhancement along the coastal areas of the NCP is attributed to the perturbation of wind fields and photolysis induced by the LULC change. The divergent variation of the MDA8 O3 concentrations in the NCP is generally caused by the variations of biogenic emissions and photolysis.

Association of Ozone Exposures with the risk of thyroid nodules in Hunan Province: a population-based cohort study

BackgroundIncreasing evidence associates air pollution with thyroid dysfunction, whereas the potential relationship between exposure to ozone (O3) and Thyroid Nodules (TNs) is unclear.MethodsThis retrospective cohort study investigated the association between O3 exposure and TNs in Hunan province, enrolling 191,357 Chinese adults who lived in Hunan province from January 2009 to December 2019 and received voluntary medical examinations. Individual exposure levels to O3 from 2010 to 2019 were measured on account of participants’ residential addresses at the district level. Associations of O3 exposure with the risk of incidental TNs were assessed by restricted cubic splines and surveyed as odds ratios after adjusting for demographic factors.ResultsIn total, 81,900 adults were newly diagnosed with TNs during the study period. Age-standardized TNs detection rate in Hunan province increased from 25.9 to 46.3% between 2010 and 2019, with the greatest annual percent change being 8.1 [95% CI, 7.3–8.8]. A similar trend has been found in all tumor sizes, ages, and both sexes. O3 exposure presented a statistically significant dose-dependent positive correlation (greater than 0.036 ppm) with TNs. Similarly, long-term exposure to high levels of O3 (1-year average O3 concentrations exceeding 0.0417 ppm) was found positively associated with increased TSH levels.ConclusionsHigh-level O3 exposure in the long term was associated with an increase in TSH. Consequently, increased TSH was related to the increased risk of TNs. Being exposed to high-level O3 in the long term was related to the increased detection rates of TNs in Hunan province, which could be mediated by TSH.

Long-term exposure to ozone and cardiovascular mortality in a large Chinese cohort.

Evidence for the association between long-term exposure to ozone (O3) and cause-specific cardiovascular disease (CVD) mortality is inconclusive, and this association has rarely been evaluated at high O3 concentrations. We aim to evaluate the associations between long-term O3 exposure and cause-specific CVD mortality in a Chinese population. From 2009 to 2018, 744,882 subjects (median follow-up of 7.72years) were included in the CHinese Electronic health Records Research in Yinzhou (CHERRY) study. The annual average concentrations of O3 and fine particulate matter (PM2.5), which were estimated using grids with a resolution up to 1×1km, were assigned to the community address for each subject. The outcomes were deaths from CVD, ischemic heart disease (IHD), myocardial infarction (MI), stroke, and hemorrhagic/ischemic stroke. Time-varying Cox model adjusted for PM2.5 and individual-level covariates was used. The mean of annual average O3 concentrations was 68.05μg/m3. The adjusted hazard ratio per 10μg/m3 O3 increase was 1.22 (95% confidence interval [CI]: 1.13-1.33) for overall CVD mortality, 1.08 (0.91-1.29) for IHD, 1.21 (0.90-1.63) for MI, 1.28 (1.15-1.43) for overall stroke, 1.39 (1.16-1.67) for hemorrhagic stroke and 1.22 (1.00-1.49) for ischemic stroke, respectively. The study showed that subjects without hypertension had a higher risk for CVD mortality associated with long-term O3 exposure (1.66 vs. 1.15, p=0.01). We observed the association between long-term exposure to high O3 concentrations and cause-specific CVD mortality in China, independent of PM2.5 and other CVD risk factors. This suggested an urgent need to control O3 pollution, especially in developing countries.

Modeling Biogenic Volatile Organic Compounds Emissions and Subsequent Impacts on Ozone Air Quality in the Sichuan Basin, Southwestern China

Biogenic volatile organic compounds (BVOCs) impact atmospheric oxidation capacity and regional air quality through various biogeochemistry processes. Accurate estimation of BVOC emissions is crucial for modeling the fate and transport of air pollutants in chemical transport models. Previous modeling characterizes the spatial variability of BVOCs while estimated BVOC emissions show large uncertainties, and the impacts of BVOC emissions on ozone (O3) air quality are not well understood. In this study, we estimate the BVOC emissions by model of emissions of gases and aerosols from nature (MEGAN) v2.1 and MEGAN v3.1 over the Sichuan Basin (SCB) situated in southwestern China for 2017. Further, the critical role of BVOC emissions on regional O3 pollution is illustrated with a CMAQ modeled O3 episode in summer 2017. Annual BVOC emissions over the SCB in 2017 are estimated to be 1.8 × 106 tons with isoprene emissions as high as 7.3 × 105 tons. Abundant BVOC emissions are depicted over the southern and southeastern SCB, in contrast to the relatively low emissions of BVOC over the Chengdu Plain and northeastern SCB. CMAQ simulations depict a strong influence of BVOC on ambient O3 formation over densely forested regions including southern SCB and Chongqing city, accounting for 10% of daily maximum hourly O3 concentration (DM1h O3) and 6% of daily maximum 8-h average O3 (MDA8h O3) concentrations in July 2017. Over the severe O3 episode in summer 2017, sensitivity experiments indicate that enhanced BVOC emissions contribute substantially to basin-wide O3 concentrations and elevate peak O3 levels by 36.5 and 31.2 μg/m3 for the southern SCB and Chengdu Plain, respectively. This work identifies robustly important effects of BVOC emissions on O3 exceedance events over the SCB and contributes insight into pursuing an O3 abatement strategy with full consideration of potential contributions from BVOC emissions.

Characteristics and Meteorological Factors of PM2.5-O3 Compound Pollution in Tianjin

The characteristics, pollutant concentration distribution, and key meteorological factors of PM2.5-O3 compound pollution in Tianjin were analyzed based on the high-resolution online monitoring data of PM2.5, O3,and meteorological data observed in Tianjin from 2013 to 2019. Total PM2.5-O3 compound pollution was 94 days and showed a decreasing trend by year; a significant decreasing trend of PM2.5-O3 compound pollution days were observed in the early stage, with a decline rate of 52.2% from 2013 to 2015. By contrast, in the later period from 2016 to 2019, a fluctuating increasing trend of PM2.5-O3 compound pollution days of 16.7% was observed. PM2.5-O3 compound pollution days mainly occurred from March to September each year with substantial variation by year, mainly occurring in June to August from 2013 to 2016 and in April and September from 2017 to 2019. The peak value of ρ(O3) (301-326 μg·m-3) appeared when ρ(PM2.5) ranged from 75 μg·m-3 to 85 μg·m-3. PM2.5-O3 compound pollution days accounted for 34.4% of total O3 pollution events in Tianjin, which showed a decreasing trend by year. The peak O3 concentration and average O3 concentration during PM2.5-O3 compound pollution were higher than those during simplex O3 pollution, and the number of days with PM2.5 and O3 as the primary pollutant decreased and increased in compound pollution days by year, respectively. The weather situation of PM2.5-O3 compound pollution was categorized into five weather types, namely low pressure, weak high pressure, rear of high pressure, front of cold front, and equalized pressure. The low pressure, front of cold front, and weak high pressure were observed most frequently, accounting for 92.5% of the total weather situation. The occurrence of PM2.5-O3 compound pollution was most probable when the dominant wind direction was the southwest and south, the average wind speed was less than 2 m·s-1, the temperature was between 20-35℃, and the humidity was between 40%-60%.

Long-term variation and evaluation of air quality across Hong Kong

Study of Air Quality Objectives (AQOs) and long-term changes of air pollution plays a decisive role in formulating and refining pollution control strategies. In this study, 10-year variations of six major air pollutants were analyzed at seven monitoring sites in Hong Kong. The continuous decrease of annual averaged concentrations of NO2, SO2, CO, PM2.5 and PM10 and numbers of days with severe pollution conditions validated the efficiency of the series of air pollution control schemes implemented by the Hong Kong government. However, there is still a big gap to meet the ultimate targets described by the World Health Organization. Besides, the concentration of O3 at roadside and urban stations increased by 135% ± 25% and 37% ± 18% from 2011 to 2020, respectively, meanwhile the highest 8 hr averaged O3 concentration was observed as 294 µg/m3 at background station in 2020, which pointed out the increasing ozone pollution in Hong Kong. There was a great decrease in the annual times of air quality health index (AQHI) laying in “high”, “very high” and “serious” categories from 2011 to 2020 with the decrease rate of 89.70%, 91.30% and 89.74% at roadside stations, and 79.03%, 95.98% and 72.73% at urban stations, respectively. Nevertheless, the number of days categorized as “high” or above at roadside station was twice more than that in the urban station during the past ten years. Thus, more policies and attentions should be given to the roadside air quality and its adverse health effect to pedestrians on street.

Regional demarcation of synergistic control for PM2.5 and ozone pollution in China based on long-term and massive data mining

Implementing an inter-regional synergistic control policy for fine particulate matter (PM2.5) and ground-level ozone (O3) could improve regional air quality. However, little is known about the effectiveness and accuracy of synergistic control region delineation. This study aimed to construct a network model and apply it to a case study of regional delineation in China at different scales to quantify the interactions between regions. Firstly, the Cumulative Risk Index (CRI) was proposed and quantified from a health risk perspective based on the daily mean PM2.5 and daily maximum 8-h average O3 concentrations from 2015 to 2020 in China. Then, the complex network topology parameters were introduced to determine the optimal threshold for different network constructions, and the Girvan–Newman (GN) algorithm was used to divide the network into independent regions. Results showed that the correlation between cities is more robust than that between provinces. There are four-seven major provincial-scale regions with strong synchronicity in CRI, suggesting that PM2.5 and O3 synergistic control policies shall be implemented jointly within these demarcated regions. Moreover, urban-scale CRI network analysis indicated that the existing key control areas (2 + 26 cities) need to be expanded to 40–50 cities and refined into seven independent urban regions. Meanwhile, the Fen–Wei Plain can be focused on six cities: Xi'an, Baoji, Xianyang, Weinan, Yuncheng, and Tongchuan. This study could improve our understanding of the synergistic control regions for PM2.5 and O3 pollution, and the results could be used to develop joint control policies for both pollutants.

A cold front induced co-occurrence of O3 and PM2.5 pollution in a Pearl River Delta city: Temporal variation, vertical structure, and mechanism

In this study, the spatiotemporal variabilities and characteristics of ozone (O3) and fine particulate matter (PM2.5) were reconstructed, and the interaction between meteorological conditions and the co-occurrence of O3 and PM2.5 in Zhuhai, a city in the Pearl River Delta (China), was analysed. The vertical distributions of lower tropospheric O3, aerosol extinction coefficient, and wind velocity were measured using a ground-based LiDAR system. The diurnal variations in air pollutant concentrations and meteorological conditions at ground level were examined from 28 November to December 8, 2020 considering the weather conditions in Zhuhai. Heavy pollution episodes with increased concentrations of O3 and PM2.5 were observed from 6 to 7 December after a period of cold air invasion. The maximum hourly average concentrations of O3 and PM2.5 at the ground level reached up to 190 μg/m3, 98 μg/m3, respectively. The horizontal wind speed rapidly decreased to less than 2 m/s during the heavy pollution episodes driven by O3 and PM2.5, whereas the vertical wind velocity was dominated by the downdraught. When the large-scale synoptic winds were weak, a strengthening sea breeze in the afternoon could promote the landward propagation of warm marine air masses, and a lower surface wind speed was driven by the convergence of cold air from the north and warm air from the south. In turn, this increased the residence time of air pollutants and promoted their conversion to secondary pollutants. Regarding the pollution sources, the results indicated that the Pearl River Estuary represented a ‘pool’ of O3 and PM2.5 pollution. In addition, the contribution of regional pollutant transport could not be ignored when considering the accumulative increase in air pollution. Overall, the relatively weak synoptic winds, low mixing height, and high generation of pollution around Zhuhai collectively resulted in high concentrations of O3 and PM2.5.

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 (NOx) was closely related to the alkene concentration, and NOx 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.

Response surface model based emission source contribution and meteorological pattern analysis in ozone polluted days

Urban and regional ozone (O3) pollution is a public health concern and causes damage to ecosystems. Due to the diverse emission sources of O3 precursors and the complex interactions of air dispersion and chemistry, identifying the contributing sources of O3 pollution requires integrated analysis to guide emission reduction plans. In this study, the meteorological characteristics leading to O3 polluted days (in which the maximum daily 8–h average O3 concentration is higher than the China Class II National O3 Standard (160 μg/m3)) in Guangzhou (GZ, China) were analyzed based on data from 2019. The O3 formation regimes and source apportionments under various prevailing wind directions were evaluated using a Response Surface Modeling (RSM) approach. The results showed that O3 polluted days in 2019 could be classified into four types of synoptic patterns (i.e., cyclone, anticyclone, trough, and high pressure approaching to sea) and were strongly correlated with high ambient temperature, low relative humidity, low wind speed, variable prevailing wind directions. Additionally, the cyclone pattern strongly promoted O3 formation due to its peripheral subsidence. The O3 formation was nitrogen oxides (NOx)-limited under the northerly wind, while volatile organic compounds (VOC)-limited under other prevailing wind directions. Anthropogenic emissions contributed largely to the O3 formation (54–78%) under the westerly, southwesterly, easterly, southeasterly, or southerly wind, but only moderately (35–47%) under the northerly or northeasterly wind. Furthermore, as for anthropogenic contributions, local emission contributions were the largest (39–60%) regardless of prevailing wind directions, especially the local NOx contributions (19–43%); the dominant upwind regional emissions contributed 12–46% (e.g., contributions from Dongguan were 12–20% under the southeasterly wind). The emission control strategies for O3 polluted days should focus on local emission sources in conjunction with the emission reduction of upwind regional sources.

Impacts of emissions along the lower Yangtze River on air quality and public health in the Yangtze River delta, China

The area along (and on) the lower Yangtze River is a hotspot in the Yangtze River Delta (YRD) due to intense anthropogenic emissions to both the water and the atmosphere. However, air emissions in the vicinity of the river have received less attention. In this study, the Community Multi-scale Air Quality (CMAQ) model and the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) were applied to quantify the impacts of air emissions in the area within 4 km of the Yangtze River (referred to as the 4 YR area) on the air quality and public health in the YRD in 2017. The 4 YR area had air pollutant emission intensities 1.6–9.6 times higher than the domain-wide averages, and contributed ∼7.5% of the annual PM2.5 concentration across the YRD. Moreover, the emissions led to widespread enhancement of the daily maximum 8-h average (MDA8) O3 concentration in the downwind areas in summer, with an average contribution of 1.5%, while titration of O3 occurred in other seasons. As a result, the emissions increased population-weighted concentration (PWC) of PM2.5 by up to 11.5 μg m−3 near the river, leading to premature mortality of ∼17,000 in the YRD. Additionally, the mortality in terms of O3 exposure was less substantial, due to the lower PWC of O3 at distances of less than 40 km from the river. The emissions were responsible for mortality of ∼6000 due to higher exposure to NO2. The results suggest that it is beneficial to public health to reduce emissions in the 4 YR area.

Estimation of the Near-Surface Ozone Concentration with Full Spatiotemporal Coverage across the Beijing-Tianjin-Hebei Region Based on Extreme Gradient Boosting Combined with a WRF-Chem Model

With the intensification of global warming and economic development in China, the near-surface ozone (O3) concentration has been increasing recently, especially in the Beijing-Tianjin-Hebei (BTH) region, which is the political and economic center of China. However, O3 has been measured in real time only over the past few years, and the observational records are discontinuous. Therefore, we propose a new method (WRFC-XGB) to establish a near-surface O3 concentration dataset in the BTH region by integrating the Weather Research and Forecasting with Chemistry (WRF-Chem) model with the extreme gradient boosting (XGBoost) algorithm. Based on this method, the 8-h maximum daily average (MDA8) O3 concentrations are obtained with full spatiotemporal coverage at a spatial resolution of 0.1° × 0.1° across the BTH region in 2018. Two evaluation methods, sample- and station-based 10-fold cross-validation (10-CV), are used to assess our method. The sample-based (station-based) 10-CV evaluation results indicate that WRFC-XGB can achieve excellent accuracy with a high coefficient of determination (R2) of 0.95 (0.91), low root mean square error (RMSE) of 13.50 (17.70) µg m−3, and mean absolute error (MAE) of 9.60 (12.89) µg m−3. In addition, superb spatiotemporal consistencies are confirmed for this model, including the estimation of high O3 concentrations, and our WRFC-XGB model outperforms traditional models and previous studies in data mining. In addition, the proposed model can be applied to estimate the O3 concentration when it has not been measured. Furthermore, the spatial distribution analysis of the MDA8 O3 in 2018 reveals that O3 pollution in the BTH region exhibits significant seasonality. Heavy O3 pollution episodes mainly occur in summer, and the high O3 loading is distributed mainly in the southern BTH areas, which will pose challenges to atmospheric environmental governance for local governments.

Determination of the background pollution in the Eastern Mediterranean applying a statistical clustering technique

The knowledge of the background air pollution is essential in order to implement abatement strategies for improving air quality. In the present study, a statistical clustering algorithm based on Hidden Markov Models (HMMs) was used to determine the background concentrations of PM10 and O3 at a coastal monitoring site in the Eastern Mediterranean by analyzing an eight-year period of air quality data, from 2011 to 2018. Time series of the deseasonalized daily average concentrations of PM10 and O3 and their diurnal amplitudes were applied to the model to identify the unobserved patterns or hidden states that define the pollution states of the two mentioned air pollutants. The pollution state characterized by the lowest daily average concentration and diurnal amplitudes defined the background pollution level and had the main interest in the current work. The findings revealed that during the studied period, 59% of the total daily PM10 values and 67% of the O3 values corresponded to the background pollution state and the average background concentrations were 14.3 ± 5.2 μg/m3 for PM10 and 48.4 ± 8.2 ppb for O3 respectively. In the case of PM10, anthropogenic activities and Saharan dust events, which define different pollution states, contribute in a decisive way to the PM10 load in the region and play a significant role in the observed annual PM10 levels. Additionally, in the case of O3, anthropogenic activities and regional pollution affect the background levels of the region mainly during summer months. The proposed method is a flexible tool with great potential for estimating the background levels of air pollutants at various monitoring stations.

Regional Transport of PM2.5 and O3 Based on Complex Network Method and Chemical Transport Model in the Yangtze River Delta, China

AbstractGround‐level ozone (O3) and atmospheric fine particulate matter (PM2.5) pollution are the major challenges for continually improving air quality in the Yangtze River Delta (YRD) region of China. Understanding regional transport patterns of PM2.5 and O3 pollution is essential for the development of regional cooperative prevention strategies. This study shows the annual concentration of PM2.5 in the YRD decreased by 18.5% from 2015 to 2018, while the mean values of the daily maximum 8‐hr average (MDA8) O3 concentration from March to October increased by 16.3%. A complex network method is utilized to investigate the regional transport of PM2.5 and O3 in different grid cells (nodes). The source apportionment method within the chemistry transport model is applied to verify the reliability of the complex network method. Interregional and intraregional transport play an important role in both PM2.5 and O3 over the YRD. The northern part of the YRD contributes much more than other areas, while the central part of the YRD, especially the southern part of Jiangsu, is the largest contributor of O3 in the YRD in the summer, accounting for about 70%. Intraregional transport plays more of a major role in increasing PM2.5 pollution than O3 pollution. This study not only verifies the transport patterns of heavy pollution through the complex network method and traditional source apportionment technology, it also reveals that both methods provide great potential in understanding transport patterns and air pollution relationships, which are the solid foundation for emission mitigation in the YRD region.

OMI formaldehyde column constrained emissions of reactive volatile organic compounds over the Pearl River Delta region of China

In recent years, surface ozone (O3) concentration was high and became the primary air pollutant in the Pearl River Delta (PRD) region. However, as precursors of tropospheric O3, the emissions of reactive nonmethane volatile organic compounds (NMVOCs) were reported to have large uncertainties. Here, combined with the simulated formaldehyde (HCHO) columns from the RAMS-CMAQ modeling system, formaldehyde (HCHO) columns derived from the Ozone Monitoring Instrument (OMI) were used as the constraints to improve the emission estimates of the reactive NMVOCs through the linear regression method over the PRD region in March of 2017. The observed highest HCHO concentration was 2–4 times as high as the original simulated results over the PRD region mostly due to the underestimation in the reactive NMVOC emissions, especially the anthropogenic sources. With the regression coefficients calculated through five sensitivity simulation cases as well as the observed HCHO column, the better quantified emissions of reactive NMVOCs were obtained over the PRD region. It showed that the total emissions of reactive NMVOCs were improved by a factor of 2.1. The emissions derived from anthropogenic, biomass burning and biogenic sources increased from 0.0329, 4.69 × 10−4 and 0.0524 Tg/month to 0.0959, 0.0215 and 0.0620 Tg/month, respectively. As a result, the difference between the observed and modeled high HCHO column decreased to 1–2.5 times, which may be dominated by the enhanced reactive NMVOC emissions derived from anthropogenic sources. Besides, the great improvement in the emissions of reactive NMVOCs contributed to an increase of 20–40 μg/m3 in the maximum daily 8-h average (MDA8) O3 concentration over the PRD region.

Spatio-Temporal Variation and Influencing Factors of Ozone Pollution in Beijing

The temporal and spatial distribution and variation characteristics of ozone (O3) in Beijing, China, are investigated using hourly monitoring data from 2020. Kriging interpolation analysis and correlation analysis are applied to describe the spatial-temporal distribution and to identify associated influencing factors. The average concentration of O3 was found to be 59.58 μg·m−3. The daily maximum sliding 8 h average ozone concentration values exceeded the primary standard (100 μg·m−3) for 129 days and exceeded the secondary standard (160 μg·m−3) for 48 days. Temporally, the general pattern of daily maximum 8 h average O3 concentration was high in spring and summer and low in autumn and winter. Monthly average values showed a maximum in June. The highest daily concentrations appeared between 13:00 and 18:00 local time, and O3 concentrations had a distinct weekly pattern of variability with daily average concentrations at weekends higher than those during working days. Spatially, annual average O3 concentrations were highest in the northeast and lowest in the southeast of the city, and the seasonal variation of O3 was most significant in the southwest of the city. In relation to city districts and counties, the annual average O3 concentrations in the Miyun District were the highest, while those in the Haidian District were the lowest. On the whole, annual average O3 concentrations in Beijing were higher in the suburbs than in central areas. Based on daily average values, there was no significant correlation between O3 concentrations and rainfall (p > 0.05), but there were significant correlations between O3 concentration and sunshine hours, wind speed, maximum temperature and minimum temperature (p < 0.05), with correlation coefficients of 0.158, 0.267, 0.724 and 0.703, respectively. O3 concentrations increased with an increasing number of sunshine hours, first increased and then decreased with increasing wind speed and increased with increasing temperature. O3 concentrations were correlated with SO2 concentrations (0.05 < p > 0.001), CO concentrations (p < 0.001) and NO2 concentrations (p < 0.001), the latter having the highest correlation coefficient of −0.553 and exhibiting opposite trends in daily and monthly variations to O3 variations. Analysis of ozone pollution sources showed that automobile exhaust, coal and oil combustion and volatile organic compounds released by industrial plants were the main sources. Terrain affected the distribution of ozone, as well as human activities and industry.

Historically understanding the spatial distributions of particle surface area concentrations over China estimated using a non-parametric machine learning method

A non-parametric ensemble model was proposed to estimate the long-term (2015–2019) particle surface area concentrations (SA) over China for the first time on basis of a vilification dataset of measured particle number size distribution. This ensemble model showed excellent cross-validation R2 value (CV R2 = 0.83) as well as a relatively low root-mean-square error (RMSE = 195.0 μm2/cm3). No matter in which year, considerable spatial heterogeneity of SA was found over China with higher SA in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Middle Lower Reaches of Yangtze River (MLYR). From 2015 to 2019, SA significantly decreased in representative city clusters. The reduction rates were 140.1 μm2·cm−3·a−1 in BTH, 110.7 μm2·cm−3·a−1 in Pearl River Delta (PRD), 105.2 μm2·cm−3·a−1 in YRD, and 92.4 μm2·cm−3·a−1 in Sichuan Basin (SCB), respectively. Even though such quick reduction, high SA (ranged from ~800 μm2/cm3 to ~1750 μm2/cm3) during the heavy pollution period (PM2.5 > 75 μg/m3) still existed in the above-mentioned city clusters and may provide rich reaction vessels for multiphase chemistry. A dichotomy of enhanced annual 4th maximum daily 8-h average O3 concentrations (4MDA8 O3) and decreased SA during summertime was found in Shanghai, a representative city of YRD. In Chengdu (SCB), increased 4MDA8 O3 concentration was associated with a synchronous increase of SA from 2017 to 2019. Differently, 4MDA8 O3 concentrations enhanced in Beijing (BTH) and Guangzhou (PRD), while not significant for SA before 2018. This work will greatly deepen our understanding of the historical variation and spatial distributions of SA over China.

Ambient ozone exposure combined with residential greenness in relation to serum sex hormone levels in Chinese rural adults

BackgroundLong-term exposure to ambient ozone (O3) and residential greenness independently relate to altered hormones levels in urban settings and developed countries. However, independent and their joint associations with progestogen and androgen were sparsely studied in rural regions. Materials and methodsA total of 6211 individuals were recruited in this study. Random forest model was applied to predict the daily average concentrations of O3 using the satellites data. Residential greenness was reflected by the normalized difference vegetation index (NDVI). Liquid chromatography-tandem mass spectrometry was used to measure serum progestogen and androgen concentrations. Gender and menopausal status modified associations of long-term exposure to O3 and residential greenness with hormones levels were analyzed by generalized linear models. ResultsLong-term exposure to O3 was negatively related to 17-hydroxyprogesterone, testosterone, and androstenedione in both men and women (premenopausal and postmenopausal); the estimated β and 95% CI of ln-progesterone in response to per 10 μg/m3 increment in O3 concentration was −0.560 (−0.965, −0.155) in postmenopausal women. Association of long-term exposure to O3 with serum androgen levels in premenopausal and postmenopausal women were alleviated by residing in places with higher greenness. Additionally, a prominent effect of long-term exposure to O3 related to decreased serum progestogen and androgen levels was found in participants with middle- or high-level of physical activity or lower education level. ConclusionsThe results suggested that long-term exposure to high levels of O3 related to decreased serum androgen levels was attenuated by living in high greenness places in women regardless of menopause status. Future studies are needed to confirm the positive health effects of residential greenness on the potential detrimental effects due to exposure to O3.

The <i>Fires, Asian, and Stratospheric Transport</i>–Las Vegas Ozone Study (<i>FAST</i>-LVOS)

Abstract. The Fires, Asian, and Stratospheric Transport–Las Vegas Ozone Study (FAST-LVOS) was conducted in May and June of 2017 to study the transport of ozone (O3) to Clark County, Nevada, a marginal non-attainment area in the southwestern United States (SWUS). This 6-week (20 May–30 June 2017) field campaign used lidar, ozonesonde, aircraft, and in situ measurements in conjunction with a variety of models to characterize the distribution of O3 and related species above southern Nevada and neighboring California and to probe the influence of stratospheric intrusions and wildfires as well as local, regional, and Asian pollution on surface O3 concentrations in the Las Vegas Valley (≈ 900 m above sea level, a.s.l.). In this paper, we describe the FAST-LVOS campaign and present case studies illustrating the influence of different transport processes on background O3 in Clark County and southern Nevada. The companion paper by Zhang et al. (2020) describes the use of the AM4 and GEOS-Chem global models to simulate the measurements and estimate the impacts of transported O3 on surface air quality across the greater southwestern US and Intermountain West. The FAST-LVOS measurements found elevated O3 layers above Las Vegas on more than 75 % (35 of 45) of the sample days and show that entrainment of these layers contributed to mean 8 h average regional background O3 concentrations of 50–55 parts per billion by volume (ppbv), or about 85–95 µg m−3. These high background concentrations constitute 70 %–80 % of the current US National Ambient Air Quality Standard (NAAQS) of 70 ppbv (≈ 120 µg m−3 at 900 m a.s.l.) for the daily maximum 8 h average (MDA8) and will make attainment of the more stringent standards of 60 or 65 ppbv currently being considered extremely difficult in the interior SWUS.

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

Background:Although short-term ozone () exposure has been associated with a series of adverse health outcomes, research on the health effects of chronic exposure is still limited, especially in developing countries because of the lack of long-term exposure estimates.Objectives:The present study aimed to estimate the spatiotemporal distribution of monthly mean daily maximum 8-h average concentrations in China from 2005 to 2019 at a 0.05° spatial resolution.Methods:We developed a machine learning model with a satellite-derived boundary-layer column, precursors, meteorological conditions, land-use information, and proxies of anthropogenic emissions as predictors.Results:The random, spatial, and temporal cross-validation of our model were 0.87, 0.86, and 0.76, respectively. Model-predicted spatial distribution of ground-level concentrations showed significant differences across seasons. The highest summer peak of occurred in the North China Plain, whereas southern regions were the most polluted in winter. Most large urban centers showed elevated levels, but their surrounding suburban areas may have even higher concentrations owing to nitrogen oxides titration. The annual trend of concentrations fluctuated over 2005–2013, but a significant nationwide increase was observed afterward.Discussion:The present model had enhanced performance in predicting ground-level concentrations in China. This national data set of concentrations would facilitate epidemiological studies to investigate the long-term health effect of in China. Our results also highlight the importance of controlling in China’s next round of the Air Pollution Prevention and Control Action Plan. https://doi.org/10.1289/EHP9406