The levels and characteristics of atmospheric metals vary in time and location, can result in various health impacts, which increases the challenge of air quality management. We aimed to investigate PM₂.₅-bound metals in multiple locations and propose a methodology for comparing metal elements across study regions and prioritizing source contributions through integrated health risk assessments. PM₂.₅-bound metals were collected in the urban, suburban, rural, and industrial regions of Taiwan between 2016 and 2018. We incorporated the positive matrix factorization (PMF) with health risk assessments (considering estimates of the margin of exposure (MOE) and excess cancer risk (ECR)) to prioritize sources for control. We found that the concentrations of Fe, Zn, V, Cu, and Mn (industry-related metals) were higher at the industrial site (Kaohsiung) and Ba, Cr, Ni, Mo, and Co (traffic-related metals) were higher at the urban site (Taipei). The rural site (Hualian) had good air quality, with low PM₂.₅ and metal concentrations. Most metal concentrations were higher during the cold season for all study sites, except for the rural. Ambient concentrations of Mn, Cr, and Pb obtained from all study sites presents a higher health risk of concern. In Kaohsiung, south Taiwan, PM₂.₅-bound metals from the iron ore and steel factory is suggested as the first target for control based on the calculated health risks (MOE < 1 and ECR > 10⁻⁶). Overall, we proposed an integrated strategy for initiating the source management prioritization of PM₂.₅-bound metals, which can aid an effort for policymaking.

Children’s respiratory health are particularly vulnerable to outdoor air pollution, but evidence is lacking on the very acute effects of air pollution on the risk of acute upper respiratory infections (AURI) and acute lower respiratory infections (ALRI) in children. This study aimed to evaluate the risk of cause-specific AURI and ALRI, in children within 24 h of exposure to air pollution. We obtained data on emergency cases, including 11,091 AURI cases (acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and unspecified acute upper respiratory infections) and 11,401 ALRI cases (pneumonia, acute bronchitis, acute bronchiolitis, unspecified acute lower respiratory infection) in Brisbane, Australia, 2013–2015. A time-stratified case-crossover analysis was used to examine the hourly association of AURI and ALRI with high concentration (95th percentile) of four air pollutants (particulate matters with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅), ozone (O₃), nitrogen dioxide (NO₂)). We observed increased risk of acute tonsillitis associated with PM₂.₅ within 13–24 h (odds ratio (OR), 1.45; 95% confidence interval [CI], 1.02–2.06) and increased risk of unspecified acute upper respiratory infections related to O₃ within 2–6 h (OR, 1.38, 95%CI, 1.12–1.70), NO₂ within 1 h (OR, 1.19; 95%CI, 1.01–1.40), and PM₂.₅ within 7–12 h (OR, 1.21; 95%CI, 1.02–1.43). Cold season and nigh-time air pollution has greater effects on AURI, whereas greater risk of ALRI was seen in warm season and daytime. Our findings suggest exposures to particulate and gaseous air pollution may transiently increase risk of AURI and ALRI in children within 24 h. Prevention measures aimed at protecting children’s respiratory health should consider the very acute effects of air pollution.

Urban turfgrass ecosystems are expected to increase at unprecedented rates in upcoming decades, due to the increasing population density and urban sprawl worldwide. However, so far urban turfgrasses are among the least understood of all terrestrial ecosystems concerning their impact on biogeochemical N cycling and associated nitrous oxide (N₂O) and nitric oxide (NO) fluxes. In this study, we aimed to characterize and quantify annual N₂O and NO fluxes from urban turfgrasses dominated by either C4, warm-season species or C3, cool-season and shade-enduring species, based on year-round field measurements in Beijing, China. Our results showed that soil N₂O and NO fluxes varied substantially within the studied year, characterizing by higher emissions during the growing season and lower fluxes during the non-growing season. The regression model fitted by soil temperature and soil water content explained approximately 50%–70% and 31%–38% of the variance in N₂O and NO fluxes, respectively. Annual cumulative emissions for all urban turfgrasses ranged from 0.75 to 1.27 kg N ha⁻¹ yr⁻¹ for N₂O and from 0.30 to 0.46 kg N ha⁻¹ yr⁻¹ for NO, both are generally higher than those of Chinese natural grasslands. Non-growing season fluxes contributed 17%–37% and 23%–30% to the annual budgets of N₂O and NO, respectively. Our results also showed that compared to the cool-season turfgrass, annual N₂O and NO emissions were greatly reduced by the warm-season turfgrass, with the high root system limiting the availability of inorganic N substrates to soil microbial processes of nitrification and denitrification. This study indicates the importance of enhanced N retention of urban turfgrasses through the management of effective species for alleviating the potential environmental impacts of these rapidly expanding ecosystems.

Particulate air pollution is a continuing challenge in China, and its adverse effects on chronic obstructive pulmonary disease (COPD) have been widely reported. However, epidemiological evidence on the associations between size-fractionated particle number concentrations (PNCs) and COPD mortality is limited. In this study, we utilized a time-series approach to investigate the associations between PNCs of particles at 0.25–10 μm in diameter and COPD mortality in Shanghai, China. Quasi-Poisson regression generalized additive models were applied to evaluate these associations, with adjustment of time trend, day of week, holidays, temperature and relative humidity. Stratification analyses were performed by season and gender. There were a total of 3238 deaths due to COPD during the study period. We found that daily COPD deaths were significantly associated with PNCs of particles <0.5 μm, and the magnitude of associations increased with decreasing particle size. An interquartile range (IQR) increase in PNC₀.₂₅—₀.₂₈, PNC₀.₂₈—₀.₃, PNC₀.₃—₀.₃₅, PNC₀.₃₅—₀.₄, PNC₀.₄—₀.₄₅ and PNC₀.₄₅—₋₀.₅ was associated with increments of 7.51% (95%CI: 2.45%, 12.81%), 7.22% (95%CI: 2.16%, 12.53%), 6.95% (95%CI: 1.81%, 12.35%), 6.26% (95%CI: 1.25%, 11.52%), 5.24% (95%CI: 0.56%, 10.13%) and 4.15% (95%CI: 0.14%, 8.32%), respectively. The associations remained robustness after controlling for the mass concentrations of gaseous air pollutants. In stratification analyses, significant associations between PNCs and COPD mortality were observed in the cold seasons, and in males. Our results suggested that particles <0.5 μm in diameter might be most responsible for the adverse effects of particulate air pollution on COPD mortality, and COPD patients are more susceptible to PM air pollution in the cold seasons, especially for males.

This study aimed to provide a comprehensive characterisation of the indoor air quality during the sleeping period of 10 couples at Lisbon dwellings, using a multi-pollutant approach, and to understand how the compliance with legislation and guidelines was to assure a good indoor air quality. The assessment of indoor air quality was conducted in the cold season using real time monitors during the sleeping period for comfort parameters (temperature and relative humidity) and air pollutants (carbon dioxide – CO₂, carbon monoxide – CO, formaldehyde – CH₂O, total volatile organic compounds – VOCs, and particulate matter – PM₂.₅ and PM₁₀), together with active sampling of bioaerosols (fungi and bacteria) before and after the sleeping period. Lower compliance (less than 50% of the cases) with the Portuguese legislation was found for temperature, CO₂ (3440 ± 1610 mg m⁻³), VOCs (1.79 ± 0.99 mg m⁻³) and both bioaerosol types. In 70% of the cases, PM₂.₅ (15.3 ± 9.1 μg m⁻³) exceeded the WHO guideline of 10 μg m⁻³. All bedrooms presented air change rates above the recommended minimum value of 0.7 h⁻¹, highlighting that a good indoor air quality during sleep is not guaranteed.

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.

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.

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.

Based on the 12-hour PM2.5 samples collected in an urban site of Beijing, sixteen PM2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) were measured to investigate the characteristics and potential source regions of particulate PAHs in Beijing. The study period included the summer period in July–August 2014, the APEC source control period during the Asia-Pacific Economic Cooperation (APEC) meeting in the first half of November 2014, and the heating period in the second half of November 2014. Compared to PM2.5, sum of 16 PM2.5-bound PAHs exhibited more significant seasonal variation with the winter concentration largely exceeding the summer concentration. Temperature appeared to be the most crucial meteorological factor during the summer and heating periods, while PM2.5-bound PAHs showed stronger correlation with relative humidity and wind speed during the APEC source control period. Residential heating significantly increased the concentrations of higher-ring-number (≥4) PAHs measured in PM2.5 fraction. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis as well as the (3 + 4) ring/(5 + 6) ring PAH ratio analysis revealed the seasonal difference in the potential source area of PM2.5-bound PAHs in Beijing. Southern Hebei was the most likely potential source area in the cold season. Using black carbon (BC) and carbon monoxide (CO) as the PAH tracers, regional residential, transportation and industry emissions all contributed to the PAH pollution in Beijing.

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.