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With the acceleration of urbanization, road dust poses a significant threat to ecological systems. To explore the source and ecological risks associated with heavy metals in surface dust, 36 road dust samples were collected in Beijing in May, August, and November 2018, and February 2019. The results indicated that the concentrations of Cd, Cr, Cu, Hg, Ni, Pb, and Zn exceeded their background values, and the mean concentration of Cd was nearly 10 times the background value. Three main sources were identified by Principal Component Analysis (PCA): industrial emissions, fuel combustion, and traffic exhaust. According to the Genetic Algorithm optimized Back Propagation (GA-BP) neural network, heavy metals from industrial sources and fuel combustion originate from suburban districts, while heavy metals from traffic exhaust originate from the city center. After careful screening of species and corresponding toxicity data, the concentration of pollutants corresponding to a 5% cumulative probability on the curve (HC5) of eight heavy metals was calculated by species sensitivity distribution (SSD), and the results indicate that most HC5 values are consistent with national standards. However, the HC5 values of Ni, Cu, and As differed from the national standards, which can be used to supplement existing standards. From the risk analysis based on HC5 values, the high-risk area of Ni (12.70–30.97%) was much larger than that of As (1.55–4.95%), and the proportions of high-risk areas of Ni and As reached their highest values in spring and autumn, respectively. Uncertainty existed between different geostatistical methods. The areas of uncertainty of Ni and As were small (less than 5.58%). The heavy metals in the surface dust in Beijing had potential ecological risks that vary with seasons and regions. Therefore, it is critical to implement targeted management measures based on pollution sources and risk distribution. [ABSTRACT FROM AUTHOR]

Numerous studies had focused on the association between air pollution and health outcomes in recent years. However, little evidence is available on associations between air pollutants and premature rupture of membranes (PROM). Therefore, we performed time-series analysis to evaluate the association between PROM and air pollution. The daily average concentrations of PM2.5, SO2 and NO2 were 54.58 μg/m3, 13.06 μg/m3 and 46.09 μg/m3, respectively, and daily maximum 8-h average O3 concentration was 95.67 μg/m3. The strongest effects of SO2, NO2 and O3 were found in lag4, lag06 and lag09, and an increase of 10 μg/m3 in SO2, NO2 and O3 was corresponding to increase in incidence of PROM of 8.74% (95% CI 2.12–15.79%), 3.09% (95% CI 0.64–5.59%) and 1.68% (95% CI 0.28–3.09%), respectively. There were no significant effects of PM2.5 on PROM. Season-specific analyses found that the effects of PM2.5, SO2 and O3 on PROM were more obvious in cold season, but the statistically significant effect of NO2 was observed in warm season. We also found the modifying effects by maternal age on PROM, and we found that the effects of SO2 and NO2 on PROM were higher among younger mothers (< 35 years) than advanced age mothers (≥ 35 years); however, ≥ 35 years group were more vulnerable to O3 than < 35 years group. This study indicates that air pollution exposure is an important risk factor for PROM and we wish this study could provide evidence to local government to take rigid approaches to control emissions of air pollutants. [ABSTRACT FROM AUTHOR]