The purpose of this study is to investigate the potential associations between air pollution and dry eye disease (DED). Data of outdoor air pollutants and meteorology as well as outpatient visits for DED were collected. A time-stratified case-crossover approach was used to analyze the associations between ambient air pollutants and outpatient visits for DED. Among the 5062 DED patients studied, 65.45% were female and 34.55% were male. In the single-pollutant model, significant associations were observed between an increase of 10 μg/m³ in the concentrations of fine-particulate matter with a median aerometric diameter of less than 10 μm (PM₁₀), fine-particulate matter with a median aerometric diameter of less than 2.5 μm (PM₂.₅), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) and outpatient visits for DED. These results were consistent with those of the multipollutant model. The strongest associations between air pollutants and patient visits were observed during the cold season and in patients aged 21–40. The significant association between air pollutants (PM₁₀, PM₂.₅, SO₂, NO₂, and CO) and DED outpatient visits indicates the importance of increased environmental protection.

Alternative transportation fuels (ATFs) can reduce air pollution. However, the influence of conventional fuels—diesel and gasoline, and particularly ATFs on photochemical air pollution is not well-characterized, limiting assessments of ATFs and air quality. This is mainly due to frequent use of lumped chemical mechanisms by related atmospheric modeling. Here we hypothesized that applying a chemical mechanism that is specifically developed according to both emission fractions and photochemical ozone creation potential of volatile organic compounds (VOCs) is key to gaining reliable insights into the impact of transportation fuels on photochemistry. We used a heterogeneous chemical mechanism with 927 reactions and relatively detailed emission inventories to specifically meet the requirements for reliable simulation of the effect of exhaust emissions from vehicles fueled by selected model fuels—diesel, gasoline, and mixtures of 15% gasoline with 85% ethanol (E85) or 85% methanol (M85)—on photochemistry. These dispersion-box model simulations revealed a strong influence of atmospheric background balance between VOCs and nitrogen oxides (NOX = [NO] + [NO2]) on the impact of exhaust emissions on photochemistry, with higher tendency toward ozone (O3) formation or destruction for more VOC-limited or NOX-limited conditions, respectively. Accordingly, higher [NOX]/[VOC] exhaust emission, such as from diesel and M85, resulted in lower O3, not only locally but also downwind of the emission. This offers a new perspective and measure for transportation fuel assessment. Rapid conversion of O3 to hydroxyl and hydroperoxyl radicals downwind of the exhaust emission indicates the importance of simulating the impact of road transportation on photochemistry at high spatial and temporal resolution. Peroxyacetyl nitrate formation was more sensitive to VOC emission under VOC-limited conditions than to NOX emission under NOX-limited conditions. Secondary formaldehyde dominated over primary emitted formaldehyde several minutes after emission. These findings should be verified using a 3D modeling study under varying meteorological conditions.

Tropospheric ozone in the surface air has become the primary atmospheric pollutant in Hangzhou, China, in recent years. Previous analysis is not enough to decode it for better regulation. Therefore, we use the traditional atmospheric model, Weather Research and Forecasting coupled with Community Multi-scale Air Quality (WRF-CMAQ), and machine learning models, Extreme Learning Machine (ELM), Multi-layer Perceptron (MLP), Random Forest (RF) and Recurrent Neural Network (RNN) to analyze and predict the ozone in the surface air in Hangzhou, China, using meteorology and air pollutants as input. We firstly quantitatively demonstrate that the dew-point deficit, instead of temperature and relative humidity, is the predominant meteorological factor in shaping tropospheric ozone. Urban heat island, daily direct solar radiation time, wind speed and wind direction play trivial role in impacting tropospheric ozone. NO₂ is the primary influential factors both for hourly ozone and daily O₃-8 h due to the titration effect. The most environmental-friendly way to mitigate the ozone pollution is to lower the volatile organic compounds (VOCs) with the highest ozone formation potentials. We deduce that the tropospheric ozone formation process tends to be not only non-linear but also non-smooth. Compared with the traditional atmospheric models, machine learning, whose characteristics are rapid convergence, short calculating time, adaptation of forecasting episodes, small program memory, higher accuracy and less cost, is able to predict tropospheric ozone more accurately.

The consequences of indoor and outdoor air pollution on human health are of great concern nowadays. In this study, we firstly evaluated indoor and outdoor air pollution levels (CO, CO₂, NO, NO₂, PM₁₀) at an urban site in Dakar city center and at a rural site. Then, the individual exposure levels to selected pollutants and the variations in the levels of biomarkers of exposure were investigated in different groups of persons (bus drivers, traders working along the main roads and housemaids). Benzene exposure levels were higher for housemaids than for bus drivers and traders. High indoor exposure to benzene is probably due to cooking habits (cooking with charcoal), local practices (burning of incense), the use of cleaning products or solvent products which are important emitters of this compound. These results are confirmed by the values of S-PMA, which were higher in housemaids group compared to the others. Urinary 1-HOP levels were significantly higher for urban site housemaids compared to semirural district ones.Moreover, urinary levels of DNA oxidative stress damage (8-OHdG) and inflammatory (interleukin-6 and -8) biomarkers were higher in urban subjects in comparison to rural ones.The air quality measurement campaign showed that the bus interior was more polluted with PM₁₀, CO, CO₂ and NO than the market and urban or rural households. However, the interior of households showed higher concentration of VOCs than outdoor sites confirming previous observations of higher indoor individual exposure level to specific classes of pollutants.

Environmentally persistent free radicals (EPFRs) are a new class of environmental risk substances that can stably exist in atmospheric particles and pose a potential threat to human health. In this study, electron paramagnetic resonance (EPR) spectroscopy was used to study the concentration levels, species characteristics, and sources of EPFRs in PM₂.₅ in Xi'an in 2017. The results showed that the concentrations of EPFRs in PM₂.₅ in Xi'an in 2017 ranged from 9.8 × 10¹¹ to 6.9 × 10¹⁴ spins/m³. The highest concentration of EPFRs occurred in winter when the average concentration was 2.1 × 10¹⁴ spins/m³. The lowest concentration of EPFRs occurred in autumn when the average concentration was 7.0 × 10¹³ spins/m³. According to the annual average atmospheric concentration of EPFRs, the amount of EPFRs inhaled by people in Xi'an is equivalent to approximately 5 cigarettes per person per day and approximately 23 cigarettes per person per day in winter when haze occurs. The results of the study on the EPFR characteristics show that the EPFRs in PM₂.₅ in Xi'an are mainly C-center organic radicals that are primarily non-decaying types, accounting for approximately 75% and 85% of total concentration of EPFRs in autumn and winter, respectively. Finally, a correlation analysis was used to explore the origins of EPFRs in PM₂.₅. Significant positive correlations were found between EPFRs and SO₂, NO₂ and the thermally derived OC3 and OC4 carbonaceous components. The results suggested that coal-fired and traffic may be important sources of EPFRs in PM₂.₅ in Xi'an. In addition, EPFRs are significantly positively correlated with O₃ in summer, suggesting that some EPFRs may also originate from secondary processes. This study provides important basic data and evidence for further assessments of the potential health risks of EPFRs in PM₂.₅ and the development of effective air pollution control measures.

Previous studies have suggested a change of birth weight linked with elevated ambient air pollutant concentrations during the pregnancy. However, investigations of the influence of higher pollutant levels on birth weight change are limited. The goal of this study is to evaluate whether the air pollution of Ningbo is associated with birth weight, and which trimester could be a window period for maternal exposure to air pollution. A total of 170,008 live births were selected in the Ningbo city of Zhejiang, China, from 2015 to 2017. We estimated the association between the decreased birth weight and the increased air pollutant concentrations in the three trimesters and full gestation. The effects of interaction among pollutants were identified using a co-pollutant adjustment model. An interquartile range increases in PM2.5 (10.55 μg/m3), SO2(4.6 μg/m3), CO (125.59 μg/m3), and O3 (14.54 μg/m3) concentrations during the entire gestation were associated with 3.65 g (95% confidence interval: −6.02 g, −1.29 g), 5.02 g (−6.89 g, −3.14 g), 2.64 g (−4.65 g, −0.63 g) and 2.9 g (−4.8 g, 1 g) decreases, respectively, in birth weight. With each interquartile range increment in NO2 concentration was associated with an 8.05 g (6.24 g, 9.85 g) increase in birth weight. In the first trimester, only the PM2.5 exposure seemed to be associated with the greatest decline in birth weight. After adjustment for co-pollutant, both PM2.5 and SO2 were still associated with birth weight, except for CO for O3 adjustment, O3 for SO2 adjustment, and O3 for NO2 adjustment. Maternal exposure to air pollution may be associated with a decrease of birth weight, but the contribution of various pollutants is necessary to verify by future research.

Global urbanisation has resulted in population densification, which is associated with increased air pollution, mainly from anthropogenic sources. One of the systems proposed to mitigate urban air pollution is urban forestry. This study quantified the spatial associations between concentrations of CO, NO₂, SO₂, and PM₁₀ and urban forestry, whilst correcting for anthropogenic sources and sinks, thus explicitly testing the hypothesis that urban forestry is spatially associated with reduced air pollution on a city scale. A Land Use Regression (LUR) model was constructed by combining air pollutant concentrations with environmental variables, such as land cover type and use, to develop predictive models for air pollutant concentrations. Traffic density and industrial air pollutant emissions were added to the model as covariables to permit testing of the main effects after correcting for these air pollutant sources. It was found that the concentrations of all air pollutants were negatively correlated with tree canopy cover and positively correlated with dwelling density, population density and traffic count. The LUR models enabled the establishment of a statistically significant spatial relationship between urban forestry and air pollution mitigation. These findings further demonstrate the spatial relationships between urban forestry and reduced air pollution on a city-wide scale, and could be of value in developing planning policies focused on urban greening.

As the frequency, intensity, and duration of heatwaves increases, emergency health serviceutilization, including ambulance service, has correspondingly increased across the world. The negative effects of air pollution on health complicate these adverse health effects. This research work is the first known study to analyze the joint effects of heatwaves and air quality on the ambulance service in Western Australia (WA). The main objective is to investigate the potential joint effects of heatwaves and air quality on the ambulance service for vulnerable populations in the Perth metropolitan area. A time series design was used. Daily data on ambulance callouts, temperature and air pollutants (CO, SO₂, NO₂, O₃, PM₁₀ and PM₂.₅) were collected for the Perth metropolitan area, WA from 2006 to 2015. Poisson regression modeling was used to assess the association between heatwaves, air quality, and ambulance callouts. Risk assessments on age, gender, socio-economic status (SES), and joint effects between heatwaves and air quality on ambulance callouts were conducted. The ambulance callout rate was higher during heatwave days (14.20/100,000/day) compared to non-heatwave days (13.95/100,000/day) with a rate ratio of 1.017 (95% confidence interval 1.012, 1.023). The ambulance callout rate was higher in males, people over 60 years old, people with low SES, and those living in coastal areas during period of heatwaves. Exposure to CO, SO₂, O₃ and PM₂.₅ increased risk on ambulance callouts and exposure to NO₂ showed joint effect with heatwave and increased risk of ambulance callouts by 3% after adjustment of all other risk factors. Ambulance callouts are an important indicator for evaluating heatwave-related emergency morbidity in WA. As the median concentrations of air pollutants in WA were lower than the Australian National Standards, the interactive effects of heatwaves and air quality on ambulance service need to be further examined, especially when air pollutants exceed the standards.

Changzhou, an industrial city in the Yangtze River Delta, has been experiencing serious haze pollution, particularly in winter. However, studies pertaining to the haze in Changzhou are very limited, which makes it difficult to understand the characteristics and formation of winter haze in this area, and develop effective control measures. In this study, we carried out continuous online observation of particulate matter, chemical components, and meteorology in Changzhou in February 2017. Our results showed that haze pollution occurred frequently in Changzhou winter and exhibited two patterns: dry haze with low relative humidity (RH) and wet haze with high RH. Water-soluble inorganic ions (SO₄²⁻, NO₃⁻, and NH₄⁺) accounted for ∼52.2% of the PM₂.₅ mass, of which sulfate was dominant in wet haze periods while nitrate was dominant in other periods. With the deterioration of haze pollution, the proportion of nitrate in PM₂.₅ increased, while sulfate proportion increased under wet haze and decreased under dry haze. Dry haze and wet haze appeared under slow north wind and south wind, respectively, and strong north wind or sea breeze scavenged pollution. We found that formation of nitrate occurred rapidly in daytime with high concentrations of odd oxygen (Oₓ = O₃ + NO₂), whereas formation of sulfate occurred rapidly during nighttime with high RH, indicating that photochemistry and heterogeneous reaction were the major formation mechanisms for nitrate and sulfate, respectively. Through the cluster analysis of 36-h backward trajectories, five sources of air masses from three directions were identified. High PM₂.₅ concentrations (84.1 μg m⁻³ on average) usually occurred under the influence of two clusters (46%) from the northwest, indicating that regional transport from northern China aggravated the winter haze pollution in Changzhou. Emission reduction, particularly the mobile sources, and regional joint prevention and control can help to mitigate the winter haze in Changzhou.

Schizophrenia is a devastating neuropsychiatric disorder with increasing concern. Limited studies have been conducted to assess the relationship between short-term exposure to ambient air pollution and schizophrenia attacks. This study aimed to investigate the associations between short-term air pollution exposure and schizophrenia outpatient visits based on a time-series study performed in China. Daily data of schizophrenia outpatient admissions and air pollution from 1 October 2010 to 31 December 2013 were collected in Xi'an, a heavily-polluted city in China. We utilized a time-series Poisson regression model to examine the associations between short-term air pollution and schizophrenia outpatient visits with different lag days. A total of 34,865 outpatient-visits for schizophrenia were identified. A 10 μg/m³ increase of PM₁₀, SO₂, and NO₂ concentrations corresponded to 0.289% (95% Cl: 0.118%, 0.460%), 1.374% (95% Cl: 0.723%, 2.025%), and 1.881% (95% Cl: 0.957%, 2.805%) elevation in outpatient-visits for schizophrenia at lag 0, and the associations appeared to be stronger, although not statistically significantly, in females and in middle and older age adults (40 and over). The most significant associations were observed on the concurrent day in different lag models. In conclusion, short-term exposure to ambient air pollution (PM₁₀, SO₂, and NO₂) can be associated with increased risk of daily outpatient visits for schizophrenia, which may contribute to the further understanding of the potential adverse effects of air pollution in schizophrenia and other neuropsychiatric disorders.