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.

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.

Air pollution is a global threat to public health, especially when considering susceptible populations, such as children. A better understanding of determinants of exposure could help epidemiologists in refining exposure assessment methods, and policy makers in identifying effective mitigation interventions. Through a participatory approach, 73 and 89 schoolchildren were involved in a two-season personal exposure monitoring campaign of equivalent black carbon (EBC) in Milan, Italy. GPS devices, time-activity diaries and a questionnaire were used to collect personal information. Exposure to EBC was 1.3 ± 1.5 μg/m³ and 3.9 ± 3.3 μg/m³ (mean ± sd) during the warm and the cold season, respectively. The highest peaks of exposure were detected during the home-to-school commute. Children received most of their daily dose at school and home (82%), but the highest dose/time intensity was related to transportation and outdoor environments. Linear mixed-effect models showed that meteorological variables were the most influencing predictors of personal exposure and inhaled dose, especially in the cold season. The total time spent in a car, duration of the home-to-school commute, and smoking habits of parents were important predictors as well. Our findings suggest that seasonality, time-activity and mobility patterns play an important role in explaining exposure patterns. Furthermore, by highlighting the contribution of traffic rush hours, transport-related microenvironments and traffic-related predictors, our study suggests that acting on a local scale could be an effective way of lowering personal exposure to EBC and inhaled dose of children in the city of Milan.

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.

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.

Measurement of atmospheric mercury speciation was conducted in a coastal city of the Yangtze River Delta, China from July 2013 to January 2014, in conjunction with air pollutants and meteorological parameters. The mean concentrations of gaseous elemental mercury (GEM), particulate bound mercury (HgP) and reactive gaseous mercury (RGM) were 3.26 ± 1.63 ng m−3, 659 ± 931 pg m−3, and 197 ± 246 pg m−3, respectively. High percentages of HgP during haze days were found, due to the increase in direct emissions and gas-particle partitioning of RGM. The average gas-particle partitioning coefficients (Kp) during moderate or severe haze days (PM2.5 > 150 μg m−3) were obviously decreased. GEM and HgP were positively correlated with PM2.5, SO2, NO2 and CO, suggesting a significant contribution of anthropogenic sources. Elevated HgP concentrations in cold seasons and in the morning were observed while RGM exhibited different seasonal and diurnal pattern. The ratio of HgP/SO2 and Pearson correlation analysis suggested that coal combustion was the main cause of increasing atmospheric Hg concentrations. The monitoring site was affected by local, regional and interregional sources. The back trajectory analysis suggested that air mass from northwest China and Huabei Plain contributed to elevated atmospheric Hg in winter and autumn, while southeast China with clean air masses were the major contributor in summer.

Driving restrictions is one policy that Beijing enforces to alleviate traffic congestion and air pollution. Based on a before-after comparative research design with general additive models (GAM), we evaluated the effects of Beijing's driving restriction policy on air pollution and public health. The results showed that driving restrictions significantly lowered the risk of hazardous pollution and brought valuable health benefits. Moreover, the health effects of the driving restriction policy were stronger in the cold season, for females and for residents above 65 years old. The findings imply that driving restrictions in Beijing offer substantial environmental and health benefits.

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.

The total PAH associated to the airborne particulate matter (PM10) was apportioned by one receptor model based on positive matrix factorization (PMF) in an urban environment (Zaragoza city, Spain) during February 2010–January 2011. Four sources associated with coal combustion, gasoline, vehicular and stationary emissions were identified, allowing a good modelling of the total PAH (R2 = 0.99). A seasonal behaviour of the four factors was obtained with higher concentrations in the cold season. The NE direction was one of the predominant directions showing the negative impact of industrial parks, a paper factory and a highway located in that direction. Samples were classified according to hierarchical cluster analysis obtaining that, episodes with the most negative impact on human health (the highest lifetime cancer risk concentrations), were produced by a higher contribution of stationary and vehicular emissions in winter season favoured by high relative humidity, low temperature and low wind speed.