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Daily PM 2.5 (particulate matter with an aerodynamic diameter of below 2.5 μm) mass concentrations were measured by gravimetric analysis in Chinese Research Academy of Environmental Sciences (CRAES), in the northern part of the Beijing urban area, from December 2013 to April 2015. Two pairs of Teflon (T1/T2) and Quartz (Q1/Q2) samples were obtained, for a total number of 1352 valid filters. Results showed elevated pollution in Beijing, with an annual mean PM 2.5 mass concentration of 102 μg/m 3 . According to the calculated PM 2.5 mass concentration, 50% of our sampling days were acceptable (PM 2.5 < 75 μg/m 3 ), 30% had slight/medium pollution (75–150 μg/m 3 ), and 7% had severe pollution (> 250 μg/m 3 ). Sampling interruption occurred frequently for the Teflon filter group (75%) in severe pollution periods, resulting in important data being missing. Further analysis showed that high PM 2.5 combined with high relative humidity (RH) gave rise to the interruptions. The seasonal variation of PM 2.5 was presented, with higher monthly average mass concentrations in winter (peak value in February, 422 μg/m 3 ), and lower in summer (7 μg/m 3 in June). From May to August, the typical summer period, least severe pollution events were observed, with high precipitation levels accelerating the process of wet deposition to remove PM 2.5 . The case of February presented the most serious pollution, with monthly averaged PM 2.5 of 181 μg/m 3 and 32% of days with severe pollution. The abundance of PM 2.5 in winter could be related to increased coal consumption for heating needs. [ABSTRACT FROM AUTHOR]

To increase the knowledge on the particulate matter of a wetland in Beijing, an experimental study on the concentration and composition of PM 10 and PM 2.5 was implemented in Beijing Olympic Forest Park from 2013 to 2014. This study analyzed the meteorological factors and deposition fluxes at different heights and in different periods in the wetlands. The results showed that the mean mass concentrations of PM 10 and PM 2.5 were the highest at 06:00–09:00 and the lowest at 15:00–18:00. And the annual concentration of PM 10 and PM 2.5 in the wetland followed the order of dry period (winter) > normal water period (spring and autumn) > wet period (summer), with the concentration in the dry period significantly higher than that in the normal water and wet periods. The chemical composition of PM 2.5 in the wetlands included NH 4 + , K + , Na + , Mg 2 + , SO 4 2 − , NO 3 − , and Cl − , which respectively accounted for 12.7%, 1.0%, 0.8%, 0.7%, 46.6%, 33.2%, and 5.1% of the average annual composition. The concentration of PM 10 and PM 2.5 in the wetlands had a significant positive correlation with relative humidity, a negative correlation with wind speed, and an insignificant negative correlation with temperature and radiation. The daily average dry deposition amount of PM 10 in the different periods followed the order of dry period > normal water period > wet period, and the daily average dry deposition amount of PM 2.5 in the different periods was dry period > wet period > normal water period. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the influence of atmospheric fine particulate matter (PM 2.5 ) pollution on indoor environment. Time series of indoor and outdoor PM 2.5 mass concentrations in a naturally ventilated building were monitored continuously and simultaneously in winter in Beijing when haze-fog episodes happen frequently. Relationships between indoor and outdoor PM 2.5 mass concentrations were examined and discussed. Indoor and outdoor PM 2.5 mass concentrations showed close correlation (R 2 = 0.9104) when the windows are closed and there are no obvious indoor particle sources. The peak values of average indoor PM 2.5 mass concentrations appeared at night, which were 1.5 times higher than the minimum values in daytime and showed an increasing trend from Monday to Friday in workdays. The indoor/outdoor PM 2.5 mass concentrations ratios (I/O ratios) are closely correlated with outdoor wind speed and relative humidity. A prediction model was developed based on a method of mathematical statistics and it was applied to estimation of indoor PM 2.5 mass concentrations by using outdoor PM 2.5 mass concentrations and meteorological parameters as inputs. There is a good agreement between model results and the measured values with correlation coefficients of R 2 = 0.95. The findings can provide meaningful reference to further research on influence of atmospheric PM 2.5 on indoor environment and help further develop approaches to control outdoor originated indoor PM 2.5 in the haze-fog episodes. [ABSTRACT FROM AUTHOR]