Air pollution could be a risk factor for the development of pterygium. This study aimed to investigate the potential associations between outpatient visits for pterygium and air pollutants. Using a time-stratified case-crossover design, the data of 3017 outpatients with pterygium visiting an eye center in Hangzhou, China, and the air pollution data of the Environmental Protection Department of Zhejiang Province between July 1, 2014, and November 30, 2019, were examined. The relationships between the air pollutants nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone, and fine particulate matter (PM) with median aerometric diameter <2.5 μm (PM₂.₅) and <10 μm (PM₁₀) and outpatient visits for primary pterygium were assessed using single- and multiple-pollutant models. Significant associations between outpatient visits for pterygium and air pollutants (PM₂.₅, PM₁₀, SO₂, and NO₂) were observed. Younger patients were found to be more sensitive to air pollution. Interestingly, the younger female patients with pterygium were more vulnerable to PM₂.₅ exposure during the warm season, while the younger male patients with pterygium were more sensitive to NO₂ during the cold season. Significant effects were also observed between the pterygium outpatients and PM₂.₅ (odds ratio [OR] = 1.06, P = 0.02), PM₁₀ (OR = 1.04, P = 0.01), and SO₂ (OR = 1.26, P = 0.01) during the warm season, as well as NO₂ (OR = 1.06, P = 0.01) during the cold season. Our study provides evidence that outpatient visits for pterygium are positively associated with increases in the air pollutants PM₂.₅, PM₁₀, SO₂, and NO₂, revealing the important role of air pollution in the occurrence and development of pterygium.

Many cities in China are currently experiencing severe air pollution due to modernization. Previous studies investigating the effects of air pollutants exposure were particularly conducted in severe air polluted area and studies in low pollution areas were sparse.To quantitatively assess the short-term effects of ambient air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) on outpatient visits in low pollution area, we conducted a time-series analysis from Jan 1, 2015 to Dec 31, 2016 in Shennongjia, China. Generalized additive model (GAM) was used to evaluate the influence of PM2.5 on daily hospital outpatient visits with different lag structures. We also conducted stratified analysis to explore the association between PM2.5 concentration and outpatient visits in different seasons.In the present study, per IQR increment of PM2.5, PM10, NO2, CO and O3 were related with 1.92% (0.76%–3.09%), 1.92% (0.77%–3.07%), 2.74% (95% CI: 1.65%–3.83%), 1.89% (95% CI: 0.68%–3.10%) and 2.30% (95% CI: 0.65%–3.95%) increase on respiratory outpatient visits. Significant associations were found between PM2.5, PM10, NO2 and respiratory outpatient visits at lag0:1, lag0:2 days. The effects of PM2.5 were more evident in the cool season than in the warm season.Our study showed that short-term exposures to PM2.5, PM10, NO2, CO and O3 were related with increased risk of outpatient visits of respiratory diseases, and highlighted the adverse effect of air pollutants exposure, especially PM2.5 exposure in cool season on health in low pollution area.

Baseline emission values of greenhouse gases were not well established for commercial poultry barns in cold regions, including Canada, due to a lack of well-designed field studies. Emission factors of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O), were acquired for a commercial broiler barn and cage-layer barn in the Canadian Prairies climate. Between March 2015 and February 2016, monthly measurements throughout the year for the layer barn and over 6 flocks for the broiler barn, and diurnal measurements in the mild, warm, and cold seasons for both barns were conducted, respectively. The ventilation rate was estimated based on a CO₂ mass balance method; thus CO₂ emissions were quantified by the CIGR (2002) models. The CH₄ and N₂O emissions present at low levels from global perspective for both barns; the cold climate proved to be a major reason for the lower CH₄ emission from the layer barn. Considerable seasonal effect was observed only for N₂O emissions from the broiler barn, and for CH₄ and N₂O emissions from the layer barn, both with higher emissions in the mild and warm seasons than in the cold season. The big diurnal variations of CO₂ emissions for the layer barn demonstrated the uncertainty of the seasonal results by snapshot measurements and correction factors (from −20.9% to −22.5%) were obtained. Besides, the difference of CH₄ and N₂O concentrations and emissions as well as CO₂ concentrations between best-case (the first day after manure removal) and worst-case conditions (the last day before manure removal) was not obvious for the layer barn. Additionally, changes of temperature and ventilation rate were likely to have more impact on N₂O emission for the broiler barn and more impact on CH₄ emission for the layer barn than on the other two gas emissions, both with positive correlations.

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Nitrogen-enriched rivers are significant sources of atmospheric N2O. This study conducted a one-year field campaign in seven N-enriched rivers draining urban, rural, and agricultural land to determine the link between the production, concentrations, and emissions of N2O and land use. Estimated N2O fluxes varied between 1.30 and 1164.38 μg N2O-N m−2 h−1 with a mean value of 154.90 μg N2O-N m−2 h−1, indicating that rivers were the net sources of atmospheric N2O. Concentrations of N2O ranged between 0.23 and 29.21 μg N2O-N L−1 with an overall mean value of 3.81 μg N2O-N L−1. Concentrations of ammonium and nitrate in urban and rural rivers were high in the cold season. The concentrations were also high in agricultural rivers in the wet season. N2O concentrations and emissions in rural and urban rivers followed a similar pattern to ammonium and a similar pattern to nitrate in agricultural rivers. A strong link between the concentrations and emissions of N2O and land use was observed. N2O concentrations in and emissions from the rivers draining the urban and rural areas were significantly higher than the rivers draining the agricultural areas (P < 0.01). Stepwise regression analysis indicated that dissolved N2O were primarily influenced by NH4+ in agricultural rivers and by NO3− in rural rivers; while dissolved N2O in urban rivers was primarily predicted by temperature and reflected the integrated impact of sewage input and river hydrology. Nitrate-N and NO3--O isotope data and linear regression of N2O and river water variables strongly indicated that dissolved N2O was mainly derived from nitrification in agricultural rivers and denitrification in rural and urban rivers.

Ambient ozone is one of the most important air pollutants with respect to its impacts on human health and its increasing concentrations globally. However, studies which explored the burden of ozone pollution on chronic obstructive pulmonary disease (COPD) and estimated the relevant economic loss were rare.We explored the relationships between ambient ozone exposure and years of life lost (YLL) from COPD mortality and estimated the relevant economic loss in Ningbo, in the Yangtze River Delta of China, 2011–2015.A time-series study was conducted to explore the effects of ozone on YLL from COPD. Seasonal stratified analyses were performed, and the effect modification of demographic factors was estimated. In addition, the related economic loss was calculated using the method of the value per statistical life year (VSLY).Averaged daily mean maximum 8-h average ozone concentration was 40.90 ppb in Ningbo, China, 2011–2015. The effect of short term ambient ozone exposure on COPD YLL was more pronounced in the cool season than in the warm season, with 10 ppb increment of ozone corresponding to 7.09(95%CI: 3.41, 10.78) years increase in the cool season and 0.31 (95%CI: −2.15, 2.77) years change in the warm season. The effect was higher in the elderly than the young. Economic loss due to excess COPD YLL related to ozone exposure accounted for 7.30% of the total economic loss due to COPD YLL in Ningbo during the study period.Our findings highlight that ozone exposure was related to tremendous disease burden of COPD in Ningbo, China. The effects were more pronounced in the cool season, and the elderly were more susceptible populations.

Ambient concentrations of fine particulate matter (PM₂.₅) concentration is often used as an exposure surrogate to estimate PM₂.₅ health effects in epidemiological studies. Ignoring the potential variations in the amount of outdoor PM₂.₅ infiltrating into indoor environments will cause exposure misclassification, especially when people spend most of their time indoors. As it is not feasible to measure the PM₂.₅ infiltration factor (Fᵢₙf) for each individual residence, we aimed to build models for residential PM₂.₅Fᵢₙf prediction and to evaluate seasonal Fᵢₙf variations among residences. We repeated collected paired indoor and outdoor PM₂.₅ filter samples for 7 continuous days in each of the three seasons (hot, cold and transitional seasons) from 48 typical homes of Shanghai, China. PM₂.₅-bound sulfur on the filters was measured by X-ray fluorescence for PM₂.₅Fᵢₙf calculation. We then used stepwise-multiple linear regression to construct season-specific models with climatic variables and questionnaire-based predictors. All models were evaluated by the coefficient of determination (R²) and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV). The 7-day mean (±SD) of PM₂.₅Fᵢₙf across all observations was 0.83 (±0.18). Fᵢₙf was found higher and more varied in transitional season (12–25 °C) than hot (>25 °C) and cold (<12 °C) seasons. Air conditioning use and meteorological factors were the most important predictors during hot and cold seasons; Floor of residence and building age were the best transitional season predictors. The models predicted 60.0%–68.4% of the variance in 7-day averages of Fᵢₙf, The LOOCV analysis showed an R² of 0.52 and an RMSE of 0.11. Our finding of large variation in residential PM₂.₅Fᵢₙf between seasons and across residences within season indicated the important source of outdoor-generated PM₂.₅ exposure heterogeneity in epidemiologic studies. Our models based on readily available data may potentially improve the accuracy of estimates of the health effects of PM₂.₅ exposure.

As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM10) classified into four grades: low (PM10 ≤ 30 μg m−3), moderate (30 < PM10 ≤ 80 μg m−3), high (80 < PM10 ≤ 150 μg m−3), and very high (PM10 > 150 μg m−3). The KME operational center generates PM10 forecasts using statistical and chemistry-transport models, but the overall performance and the hit rate for the four PM10 grades has not previously been evaluated. To provide a statistical reference for the current air quality forecasting system, we have developed a neural network model based on the synoptic patterns of several meteorological fields such as geopotential height, air temperature, relative humidity, and wind. Hindcast of the four PM10 grades in Seoul, Korea was performed for the cold seasons (October–March) of 2001–2014 when the high and very high PM10 grades are frequently observed. Because synoptic patterns of the meteorological fields are distinctive for each PM10 grade, these fields were adopted and quantified as predictors in the form of cosine similarities to train the neural network model. Using these predictors in conjunction with the PM10 concentration in Seoul from the day before prediction as an additional predictor, an overall hit rate of 69% was achieved; the hit rates for the low, moderate, high, and very high PM10 grades were 33%, 83%, 45%, and 33%, respectively. Our findings also suggest that the synoptic patterns of meteorological variables are reliable predictors for the identification of the favorable conditions for each PM10 grade, as well as for the transboundary transport of PM10 from China. This evaluation of PM10 predictability can be reliably used as a statistical reference and further, complement to the current air quality forecasting system.

One year sampling (2011–2012) campaign of airborne PM2.5-bound PAH was performed in Zaragoza, Spain. A source apportionment of total PAH by Positive Matrix Factorization (PMF) was applied in order to quantify potential PAH pollution sources.Four sources were apportioned: coal combustion, vehicular emissions, stationary emissions and unburned/evaporative emissions. Although Directive 2004/107/EC was fulfilled regarding benzo(a)pyrene (BaP), episodes exceeding the limit value of PM2.5 according to Directive 2008/50/EC were found. These episodes of high negative potential for human health were studied, obtaining a different pattern for the exceedances of PM2.5 and the lower assessment threshold of BaP (LATBaP). In both cases, stationary emissions contributed majority to total PAH. Lifetime cancer risk exceeded the unit risk recommended by the World Health Organization for those episodes exceeding the LATBaP and the PM2.5 exceedances for the warm season. For the cold season, the risk was higher for the LATBaP than for the PM2.5 exceedances.

This study aimed to investigate the effects of dust–haze on mortality and to estimate the seasonal and individual-specific modification effects in Guangzhou, China. Mortality, air pollution and meteorological data were collected for 2006–2011. A dust–haze day was defined as daily visibility <10 km with relative humidity <90%. This definition was further divided into light (8–10 km), medium (5–8 km) and heavy dust–haze (<5 km). A distributed lag linear model (DLM) was employed. Light, medium and heavy dust–haze days were associated with increased mortality of 3.4%, 6.8% and 10.4% respectively, at a lag of 0–6 days. This effect was more pronounced during the cold season, for cardiovascular mortality (CVD), respiratory mortality (RESP), in males and people ≥60years. These effects became insignificant after adjustment for PM10. We concluded that dust–haze significantly increased mortality risk in Guangzhou, China, and this effect appears to be dominated by particulate mass and modified by season and individual-specific factors.

Levoglucosan was present in all samples and its concentrations showed a pronounced annual cycle with maximum levels in the cold season. The annual percentage of ratios of levoglucosan to OC ranged from 0.04 to 9.75% evidencing a major contribution of biomass burning to the aerosol OC during the winter. In the urban-background site, OC was strongly correlated with EC in winter, suggesting that the major fraction of OC was generated as primary particles along with EC. A background levoglucosan component showed that biomass burning was continuously taking place in all the investigated sites. The biomass burning contribution to the Tuscany aerosol was made up of a background component and an additional component during winter probably due to wood burning for domestic heating.