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Airborne bacteria are important components of fine particulate matter (PM 2.5), and have received increasing attention because of their impacts on public health and ecological systems. However, the relationships between the bacterial community and PM 2.5 pollution are poorly understood. The properties of bacterial communities in Beijing at low, medium and high PM 2.5 levels were analyzed during winter (December 2015–January 2016; January 2017) and spring (March 2016–May 2016; April 2017–May 2017). Variations in bacterial concentrations, Shannon and Simpson indices and relative abundance were significantly related to the seasons. In winter, there were no significant differences in bacterial communities among three PM 2.5 pollution levels. In contrast, significant correlations between bacterial abundance and PM 2.5 levels were observed in spring, and the bacterial concentrations, community richness and diversity indices were significantly higher on heavily polluted days compared to other pollution levels. Correlation results showed that relative humidity (RH), wind speed (WS), and O 3 were most closely associated with microbial community structure in winter (P < 0.05), but temperature (T), NO 2 , SO 2 , and CO in spring, while CO, NO 2 , O 3 , RH, and WS had significant relationships (|r| = 0.360–0.553, P < 0.05) with bacterial concentrations in winter, but PM 2.5 , O 3 , T, and RH (|r| = 0.281–0.527, P < 0.05) in spring. Chemical composition, especially that of secondary aerosol particles, which were mainly produced from anthropogenic sources (e.g. fossil fuel combustion, road traffic and industrial emissions), exerted the most control of bacterial community structure of PM 2.5. The effects of PM 2.5 levels on the bacterial community were modified by environmental conditions, heavy metal and nutrient contents of the PM 2.5. The relationships described provide a foundation for further research into the environmental and PM 2.5 chemical composition controls on the bacterial community and related health risk from air pollution. [Display omitted] • Conditional responses of bacterial communities to PM 2.5 pollution. • Stable bacterial communities across different PM 2.5 levels in winter. • Significant changes of bacterial communities to PM 2.5 levels in spring. • Secondary aerosol particles exerted the most control of bacterial community structure. [ABSTRACT FROM AUTHOR]

In order to cope with heavy haze pollution in Beijing, the Air Pollution Prevention and Control Action Plan was issued in 2013. In this study, we took January observations from 2014 to 2018 as a case study to assess wintertime air quality improvement in Beijing after five years of continuous emission control measures and to investigate the causes of haze formation. SO 2 and NO 2 concentrations in January 2018 decreased by 84% and 41% from January 2014, while NH 3 concentrations remained relatively stable during these years with an average of 7.28 μg m−3. The mean concentrations of PM 2.5 and water-soluble inorganic ions declined over the study period, while compared with 2014, decreased SO 4 2− ratio and increased NO 3 − contribution in PM 2.5 were observed, highlighting the importance of reactive nitrogen (Nr) pollution control. High concentrations of NH 3 , NO 2 , as well as NH 4 + and NO 3 − in PM 2.5 at roadside monitoring sites, indicated that vehicle sources played a vital role in local urban Nr emissions. Finally, we found most NH 3 existed in the gas phase in the Beijing atmosphere, even on polluted winter days, suggesting a considerable risk for additional secondary aerosol formation. Our findings demonstrate the effectiveness of the emissions control in alleviating Beijing's air pollution. Significant reductions of precursor emissions are needed to achieve the goals set by air quality standards in the future, especially for NH 3. It is especially crucial to jointly consider and control multiple pollution sources to effectively reduce the high levels of air pollution that remain in Beijing. • Significant improvements in Beijing air quality were observed during January 2014 to 2018. • The concentrations of SO 2 , NO 2 in air and SO 4 2−, NO 3 −, NH 4 + in PM 2.5 significantly decreased. • NH 3 concentrations remained stable during these 5 years. • Vehicle sources are vital contributors to NH 3 and NO 2 emissions. • The Beijing atmosphere is NH 3 -rich. [ABSTRACT FROM AUTHOR]

Identifying the sources of increased ammonia (NH 3) in the atmosphere has important implications for air quality, ecosystems, and climate. While analysis of the nitrogen isotopic composition (δ15N) can aid in the apportionment of NH 3 emission sources, the widely-used passive collection methods have not been verified for their ability to accurately characterize δ15N-NH 3. In this study, three types of passive samplers (ALPHA, Analyst, and Radiello) were employed and collocated with a denuder based active sampler (DELTA, serves as a reference method) to compare and contrast their ability in collecting atmospheric NH 3 for subsequent concentration and δ15N-NH 3 analysis in urban Beijing during the summer of 2018. The results showed that NH 3 concentrations determined using passive collection samplers that included ALPHA (n = 11), Analyst (n = 12), and Radiello (n = 7) samplers were 13.4%, 14.4%, and 27.5% lower than that of the active sampler (n = 12), respectively. The low NH 3 concentration bias in the passive collection samplers was suggested to be the result of inaccurate effective sampling rates due to incorrect mass transfer correction factors for the environmental conditions of this study. The δ15N-NH 3 values did not show significant differences between passive samplers, with weekly means of −31.0 ± 1.0‰ (n = 4), −28.4 ± 5.5‰ (n = 4), and −29.1 ± 0.9‰ (n = 4) for the ALPHA, Analyst, and Radiello, respectively. Notably, the overall mean δ15N-NH 3 values collected by these passive samplers (−29.5 ± 3.2‰, n = 12) was significantly lower than that of the active sampler (−14.1 ± 1.6‰, n = 4), with a difference of 15.4 ± 3.5‰. The large underestimation of δ15N-NH 3 values by passive samplers can be explained by the diffusive isotope fractionation of NH 3 isotopologues, which is driven by relative mass differences of 14NH 3 and 15NH 3. Overall, these findings highlight a potential low bias in NH 3 concentrations and a substantial uncertainty in previous source interpretation using δ15N-NH 3 as previous studies have almost exclusively characterized δ15N-NH 3 using passive samplers. We suggest that the denuder-based active sampler should be used in the future for characterizing δ15N-NH 3 whether at the source or in an atmospheric environment with mixed sources. This work also has important implications for characterizing δ15N of other gaseous nitrogen compounds. Unlabelled Image • Nitrogen isotopic composition of ammonia (δ15N-NH 3) aids in source apportionment. • Conventional collection methods for δ15N-NH 3 were almost based on passive samplers. • δ15N-NH 3 obtained by passive and active samplers were respective −29.5‰ and −14.1‰. • The low bias of 15.4‰ by passive δ15N-NH 3 was due to diffusive isotope fractionation. • Source apportionment based on passive δ15N-NH 3 might mislead mitigation strategy. [ABSTRACT FROM AUTHOR]