Current evidence suggests that airborne pollutants have a detrimental effect on fetal growth through the emergence of small for gestational age (SGA) or term low birth weight (TLBW). The study\'s objective was to critically evaluate the available literature on the association between environmental pollution and the incidence of SGA or TLBW occurrence. A comprehensive literature search was conducted across Pubmed/MEDLINE, Web of Science, Cochrane Library, EMBASE, and Google Scholar using predefined inclusion and exclusion criteria. The methodology adhered to the PRISMA guidelines. The systematic review protocol was registered in PROSPERO with ID number: CRD42022329624. As a result, 69 selected papers described the influence of environmental pollutants on SGA and TLBW occurrence with an Odds Ratios (ORs) of 1.138 for particulate matter ≤ 10 μm (PM10), 1.338 for particulate matter ≤ 2.5 μm (PM2.5), 1.173 for ozone (O3), 1.287 for sulfur dioxide (SO2), and 1.226 for carbon monoxide (CO). All eight studies analyzed validated that exposure to volatile organic compounds (VOCs) is a risk factor for SGA or TLBW. Pregnant women in the high-risk group of SGA occurrence, i.e., those living in urban areas or close to sources of pollution, are at an increased risk of complications. Understanding the exact exposure time of pregnant women could help improve prenatal care and timely intervention for fetuses with SGA. Nevertheless, the pervasive air pollution underscored in our findings suggests a pressing need for adaptive measures in everyday life to mitigate worldwide environmental pollution.

UNASSIGNED: There is a growing body of evidence suggesting a causal relationship between interstitial lung disease (ILD) and air pollution, both for the development of the disease, and driving disease progression. We aim to provide a comprehensive literature review of the association between air pollution, and ILD, including idiopathic pulmonary fibrosis (IPF).
UNASSIGNED: We systematically searched from six online database. Two independent authors (DL and CF) selected studies and critically appraised the risk of bias using the Newcastle-Ottawa Scale (NOS). Findings are presented through a narrative synthesis and meta-analysis. Meta-analyses were performed exclusively when there was a minimum of three studies examining identical pollutant-health outcome pairs, all evaluating equivalent increments in pollutant concentration, using a random effects model.
UNASSIGNED: 24 observational studies conducted in 13 countries or regions were identified. Pollutants under investigation encompassed ozone (O3), nitrogen dioxide (NO2), Particulate matter with diameters of 10 micrometers or less (PM10) and 2.5 micrometers or less (PM2.5), sulfur dioxide (SO2), carbon monoxide (CO), nitric oxide (NO) and nitrogen oxides (NOx). We conducted meta-analyses to assess the estimated Risk Ratios (RRs) for acute exacerbations (AE)-IPF in relation to exposure to every 10 μg/m3 increment in air pollutant concentrations, including O3, NO2, PM10, and PM2.5. The meta-analysis revealed a significant association between the increased risk of AE-IPF in PM2.5, yielding RR 1.94 (95% CI 1.30-2.90; p = 0.001). Findings across all the included studies suggest that increased exposure to air pollutants may be linked to a range of health issues in individuals with ILDs.
UNASSIGNED: A scarcity of available studies on the air pollutants and ILD relationship underscores the imperative for further comprehensive research in this domain. The available data suggest that reducing levels of PM2.5 in the atmosphere could potentially reduce AE frequency and severity in ILD patients.

An atmospheric-pressure spatial atomic layer deposition system operated in atmospheric-pressure spatial chemical vapor deposition conditions is employed to deposit alumina (AlOx) thin films using trimethylaluminum and different oxidants, including water (H2O), hydrogen peroxide (H2O2), and ozone (O3). The impact of the oxygen precursor on the structural properties of the films and their moisture-barrier performance is investigated. The O3-AlOxfilms, followed by H2O2-AlOx, exhibit higher refractive indexes, lower concentrations of OH- groups, and lower water-vapor-transmission rates compared to the films deposited using water (H2O-AlOx). The AlOxfilms are then rapidly deposited as thin-film-encapsulation layers on perovskite solar cells at 130 °C without damaging the temperature-sensitive perovskite and organic materials. The stability of thep-i-nformamidinium methylammonium lead iodide solar cells under standard ISOS-D-3 testing conditions (65 °C and 85% relative humidity) is significantly enhanced by the encapsulation layers. Specifically, the O3-AlOxand H2O2-AlOxlayers result in a six-fold increase in the time required for the cells to degrade to 80% of their original efficiency compared to un-encapsulated cells.

In recent years, the situation of ozone pollution in China has become increasingly severe, with PM2.5 being the main pollutant in the atmospheric environment of several cities. Meteorological conditions, particularly temperature and humidity, have a great influence on ozone formation. Therefore, understanding and quantifying the impact of the variation in temperature and humidity on ozone level can effectively provide the theoretical basis for the government to prevent and control ozone pollution. By analyzing the relationship among the daily maximum temperature (Tmax), relative humidity (RH), and the maximum 8-h running average ozone (O3-8h) measured from January 1, 2015 to July 31, 2022, a linear positive correlation between O3-8h and Tmax was observed in the seven regions with serious ozone pollution, and the temperature penalty factor ranged from 2.1-6.0 μg·(m3·℃)-1; a nonlinear correlation between O3-8h and RH was also observed, and O3-8h was the highest when RH was 55%. The sensitivity of different regions to Tmax and RH was slightly different; generally, the most suitable meteorological conditions for ozone formation were 29℃ ≤ Tmax< 38℃ and 40% ≤ RH<70%. In the Yangtze River Delta, Jiangsu-Anhui-Shandong-Henan, and the middle reaches of the Yangtze River, under extreme high temperature conditions (Tmax ≥ 35℃), O3-8h stopped increasing with the increase in temperature and even dropped; simultaneously, it was often accompanied with a small increase in particulate matter. It may be related to the heterogeneous reaction of some precursors with higher water vapor content and the increase in ozone heterogeneous sink.

Based on OMI remote sensing satellite data, the temporal and spatial characteristics of tropospheric ozone (O3), nitrogen dioxide (NO2), and formaldehyde (HCHO) concentrations in East China from 2005 to 2021 were analyzed, and the backward trajectory (HYSPLIT) model was used to explore their sources. The results showed that ① during the 17 years, the tropospheric O3 concentration steadily increased, reached the maximum value in 2010, and then showed a fluctuating and undulating state. NO2 showed an increasing trend from 2005 to 2012 and slowly decreased from 2012 to 2021. The average HCHO concentration showed an increasing trend from 1.15×1016molec·cm-2 in 2005 to 1.8×1016 molec·cm-2 in 2021. ② In terms of spatial characteristics, the concentrations of the three pollutants generally showed a pattern of high concentration in the north and low concentration in the south, with a high concentration in the north, uncharacteristic concentration in the middle, and low concentration in the south. ③ The sensitivity of O3 was as follows:η<2.3 in spring, which belonged to the VOCs control area; η<4.2 in summer, showing that most areas were NOx-VOCs coordinated control areas and a few areas were VOCs control areas; η<4.2 in autumn, which was primarily controlled by VOCs, with a few of them being NOx-VOC synergistic control areas; and η<2.3 in winter, which was a VOCs-controlled area. VOCs were primarily controlled in Shandong Province. ④ Owing to the high concentration of O3 in Shandong Province from 2005 to 2021, Jinan, the capital city of Shandong Province in 2021, was selected for ozone source analysis. The O3 concentration increased in Jinan in 2021 owing to two aspects. First, the long-distance air transportation primarily originated from Lianyungang City in Jiangsu Province and Cangzhou City in Hebei Province. Second, the close air mass transport originated from the pollution of cities near Jinan and the economic zones of the Yellow Sea and Bohai Sea, and the aggregation analysis results corresponded with those of the potential source contribution factor algorithm (PSCF) and the weighted trajectory analysis (CWT).

Based on ambient air quality data, meteorological observation data, and satellite remote sensing data, the temporal and spatial variations in ozone (O3) pollution, the sensitivity of O3, and its relationship with meteorological factors in Hainan Island were analyzed in this study. The results showed that the maximum daily 8-h moving mean (O3-8h) in western and northern cities in Hainan Island was higher than that in the central, eastern, and southern cities. O3-8h was the highest in 2015, and O3-8h exceeding the standard proportion was the largest in 2019. In addition, O3-8h was positively correlated with average temperature (P<0.1), sunshine duration (P<0.01), total solar radiation (P<0.01), atmospheric pressure, and average wind speed and was negatively correlated with precipitation (P<0.05) and relative humidity. The satellite remote sensing data showed that the tropospheric NO2 column concentration (NO2-OMI) and HCHO column concentration (HCHO-OMI) displayed opposite trends in Hainan Island from 2015 to 2020. Compared with those in 2015, NO2-OMI increased by 7.74% and HCHO-OMI decreased by 10.2% in 2020. Moreover, Hainan Island belongs to the NOx control area, and the FNR value exhibited a fluctuating downward trend in the past 6 years, with a trend coefficient and climatic trend rate of -0.514 and -0.123 a-1, respectively. A strong correlation was observed between meteorological factors and the FNR value of Hainan Island.

The \"14th Five-Year Plan\" period is the key stage for southern Hebei cities (Shijiazhuang, Xingtai, and Handan) to be removed from the bottom ten of the Air Quality Composite Index. The hourly ozone (O3) data of 15 country-controlled monitoring stations in the southern cities of Hebei Province from April to October 2020, hourly data of three volatile organic compound (VOCs) supersites, and the meteorological data of the same period were used for analysis, combined with the spatiotemporal succession, O3 formation potential (OFP), backward trajectory modeling, and spatial statistical modeling. The results showed the following:firstly, the temporal variations in O3 in southern cities of Hebei Province from April to October presented an inverted \"U\" shape, and the spatial distribution was high in the south and low in the north. O3 pollution was the most serious in June, with Xingtai (233.8 μg·m-3)>Handan (225.2 μg·m-3)>Shijiazhuang (224.8 μg·m-3). O3 was positively correlated with temperature and wind speed and negatively correlated with humidity and VOCs; furthermore, the ρ(TVOC) from April to October followed the order of Xingtai (274 μg·m-3)>Shijiazhuang (266 μg·m-3)>Handan (218 μg·m-3). The total OFP of alkenes and aromatics accounted for more than half; moreover, the trajectory of O3 pollution in southern cities of Hebei Province showed spatial directionality and relevance. The highest mass concentration of O3 (198.92 μg·m-3) was in the trajectory from Shijiazhuang to Xingtai, and the highest frequency of O3 pollution was in the trajectory from Handan to Xingtai. Moreover, the transmission contributions of O3from Xingtai to Shijiazhuang agglomerations were high (27.39%), and Handan played a significant role in the transmission contribution of O3 to Xingtai (32.76%).

High levels of fine particulate matter (PM2.5) and ozone (O3) in ambient air affect climate change and also endanger human health and ecosystems. Air pollution in Nanjing has been improving since the implementation of the \"Air Pollution Prevention and Control Action Plan\" in 2013. However, Nanjing still faces PM2.5 and O3 pollution. Evaluating the response of pollutant concentrations to the reductions in precursor emissions is helpful to obtain effective strategies of emission reduction to improve pollution levels. The sensitive simulations of emission perturbation in atmospheric chemistry models directly demonstrate the response of pollution to the reductions in emissions. Nevertheless, these sensitive simulations are limited in computing time and resources. The random forest algorithm was trained by using the simulation results of the atmospheric chemical transport model (GEOS-Chem) in 2015. The changes in daily PM2.5 and daily maximum eight-hour O3 (MDA8 O3) concentrations in Nanjing in 2019 were efficiently predicted under different reduction scenarios of anthropogenic emissions. The simulations showed that the seasonal average of ρ(PM2.5) in Nanjing would decrease by 2-4 μg·m-3 with the reduction in anthropogenic emissions of 10% in 2019 in China. In the case of controlling only local emissions in Nanjing, the concentrations of PM2.5 in Nanjing decreased significantly without local anthropogenic emissions. Additionally, the simulations showed that the annual average of ρ(PM2.5) in Nanjing could be lower than the national secondary limit (35 μg·m-3) when the anthropogenic emission reduction in China was higher than 20% in 2019. For ozone, the equal proportional emission reductions in nitrogen oxides (NOx) and volatile organic pollutants (VOCs) of O3 precursors in China likely led to the increase in seasonal average concentrations of O3 in Nanjing. For the proportional reduction of anthropogenic emissions by 10%-50% in China, the seasonal average of ρ(MDA8 O3) in Nanjing in 2019 would increase by 1-3 μg·m-3 in spring, 1-4 μg·m-3 in autumn, and 3-11 μg·m-3 in winter, respectively, compared with that in the base simulation. With the reduction in anthropogenic NOx emission by 10% and VOCs by 20%, the seasonal average of ρ(MDA8 O3) in Nanjing would decrease by 3-6 μg·m-3. On this basis, further increasing the proportion (30%) of VOCs emission reduction could reduce the annual average of ρ(MDA8 O3) in Nanjing by 7 μg·m-3. However, the annual average of ρ(MDA8 O3) of Nanjing in 2019 increased by 1 μg·m-3, with the local emission reduction of NOx by 10% and VOCs by 30%. Therefore, this showed that the key to alleviate ozone pollution in Nanjing is a reasonable control ratio of ozone precursor emissions and the implementation of regional joint prevention and control. In order to effectively reduce the O3 pollution in Nanjing, the emission reduction ratio of NOx and VOCs in China should be less than 1:2. The response of pollutant concentrations to reductions in precursor emissions were efficiently obtained by the random forest algorithm and GEOS-Chem model. The simulations would provide the scientific basis for the emission control strategy to alleviate air pollution.

The change trend, relationship, and influencing factors of PM2.5 and O3 concentrations were analyzed by using a Kolmogorov-Zurbenko (KZ) filter coupled with stepwise multiple linear regression analysis and the spatiotemporal resolution monitoring data of PM2.5 and O3 and meteorological data observed in Tianjin from 2013 to 2020. The results showed that a significant decreasing trend of PM2.5 concentrations by 50.0% was observed from 2013 to 2020, whereas an increasing trend for O3 concentrations by 25.8% was observed from 2013 to 2020. Compared with that in 2013 to 2017, the monthly difference in PM2.5 concentrations gradually narrowed from 2018 to 2020, whereas the concentration of O3 had increased significantly since April, and the occurrence time of O3 pollution was advanced. The correlation coefficient patterns of O3 and PM2.5 showed obvious seasonal distribution characteristics. The correlation coefficients were negatively correlated in winter and positively correlated in the summer, and the correlation coefficients in summer were generally higher than those in other seasons. The correlation coefficients between O3 and PM2.5 in different seasons were positively proportional to the fitting slope. The ratios of the fitting slope to correlation coefficients showed an increasing trend, which might reflect that the inhibitory effect of PM2.5 on O3 formation in the PM2.5-O3 interaction mechanism might have been weakened due to the impact of emission reduction. A significant decreasing trend was observed for the long-term trend components of the PM2.5 concentration time series; emission reduction played a leading role, and meteorological factors contributed -3 to 6 μg·m-3. The changes in the relationship between the PM2.5/CO ratio versus NO2/SO2 from negative to positive were observed from 2013-2017 to 2018-2020 in Tianjin, which could indicate the enhanced contribution potential of nitrogen oxides to the main secondary component formation of PM2.5 under the current emission reduction scenarios, and the main secondary components of PM2.5in Tianjin gradually changed from sulfate to nitrate. An overall upward trend was observed for the long-term trend components of the O3 concentration time series from 2013 to 2020, and the contribution of precursor emissions to the long-term component of O3 increased from 2013 to 2018 and began to decrease after 2019. The contribution of meteorological factors to the long-term component of O3 presented an obvious stage change, showing a downward trend from 2013 to 2016 and an upward trend from 2016 to 2020. The O3 concentration presented a non-linear relationship with NO2 during the period of intense atmospheric photochemical processes (11:00-16:00) in summer. Compared with that in 2013-2015, the fitting curve of O3 and NO2 showed an obvious offset to the low value of NO2 from 2016 to 2020, which reflected that the NOx emission reduction in this period achieved certain results. Compared with that in 2018, the fitting curve of O3 and NO2 moved downward from 2019 to 2020, which may reflect that NOx and VOCs emission reduction had a non-negligible effect on the O3 decline at this stage.

Ozone (O3) pollution in Hunan province has become the most important factor among the six common conventional pollutants (i.e., NO2, SO2, CO, O3, PM10, and PM2.5) in the atmospheric environment. Further investigation has indicated that the relevant studies of O3 are insufficient. Therefore, it is essential to clarify the key driving factors of O3 variations for government regulators. In this study, a combined method consisting of a generalized additive model (GAM), empirical orthogonal function (EOF), and absolute principal component scores (APCs) model was employed to identify and quantify the impacts of meteorology and local photochemical generation (local) and that transported from outside (nonlocal) on O3 variations from 2018-2020. Simultaneously, the driving factors of O3 annual values from 2018 to 2019 and from 2019 to 2020 in Changsha were analyzed. The results showed that O3 episodes were commonly caused by meteorology when the relative contribution from precursors was high, on the short-term time scale. Overall, on the temporal scale, meteorology and local were the driving factors for the increasing annual O3 from 2018 to 2019. Additionally, the contribution from meteorology, local, and nonlocal decreased from 2019 to 2020, leading to a lower level of O3 concentration in 2020. Geographically, the east, north, and south of Changsha were mainly affected by meteorology, local, and nonlocal, respectively. Throughout the three years, nonlocal exhibited a sustained decreasing trend, whereas the tendencies from meteorology and local varied by year and geography. Local contribution in the north of Changsha increased from 2018 to 2019, which was likely attributed to the increasing biogenic volatile organic compound emission (BVOCs), and it became lower in the south owing to the strengthened consumption by NOx. Impacts from meteorology on O3 in all sites were enhanced from 2018 to 2019. By contrast, local contribution decreased in the north and increased in the south with the decline in BVOC and NOx emissions from 2019 to 2020, when the meteorological impacts on O3 in the whole area became weak.