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Polyhalogenated carbazoles (PHCZs) are recently raising much attention due to their toxicity and ubiquitous environmental distribution. However, little knowledge is known about their ambient occurrences and the potential source. In this study, we developed an analytical method based on GC-MS/MS to simultaneously determine 11 PHCZs in PM 2.5 from urban Beijing, China. The optimized method provided low method limit of quantifications (MLOQs, 1.45-7.39 fg/m 3 ) and satisfied recoveries (73.4%-109.5%). This method was applied to analyze the PHCZs in the outdoor PM 2.5 (n = 46) and fly ash (n = 6) collected from 3 kinds of surrounding incinerator plants (steel plant, medical waste incinerator and domestic waste incinerator). The levels of ∑ 11 PHCZs in PM 2.5 ranged from 0.117 to 5.54 pg/m 3 (median 1.18 pg/m 3 ). 3-chloro-9H-carbazole (3-CCZ), 3-bromo-9H-carbazole (3-BCZ), and 3,6-dichloro-9H-carbazole (36-CCZ) were the dominant compounds, accounting for 93%. 3-CCZ and 3-BCZ were significantly higher in winter due to the high PM 2.5 concentration, while 36-CCZ was higher in spring, which may be related to the resuspending of surface soil. Furthermore, the levels of ∑ 11 PHCZs in fly ash ranged from 338 to 6101 pg/g. 3-CCZ, 3-BCZ and 36-CCZ accounted for 86.0%. The congener profiles of PHCZs between fly ash and PM 2.5 were highly similar, indicating that combustion process could be an important source of ambient PHCZs. To the best of our knowledge, this is the first research providing the occurrences of PHCZs in outdoor PM 2.5 ., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report., (Copyright © 2022. Published by Elsevier B.V.)

During the SARS period in 2003 and COVID-19 pandemic period in 2020, unexpected severe particulate matter pollution occurred in northern China, although the anthropogenic activities and associated emissions have assumed to be reduced dramatically. This anomalistic increase in PM 2.5 pollution raises a question about how source emissions impact the air quality during these pandemic periods. In this study, we investigated the stable Cu and Si isotopic compositions and typical source-specific fingerprints of PM 2.5 and its sources. We show that the primary PM 2.5 emissions (PM 2.5 emitted directly from sources) actually had no reduction but redistribution during these pandemic periods, rather than the previous thought of being greatly reduced. This finding provided critical evidence to interpret the anomalistic PM 2.5 increase during the pandemic periods in north China. Our results also suggested that both the energy structure adjustment and stringent regulations on primary emissions should be synergistically implemented in a regional scale for clean air actions in China.

Organophosphate esters (OPEs) in atmospheric fine particles (PM 2.5 ) were comprehensively investigated in the Beijing-Tianjin-Hebei (BTH) region from April 2016 to March 2017. The concentrations of Σ 8 OPEs in all the five sampling sites ranged from 90 to 8291 pg/m 3 (mean 1148 ± 1239 pg/m 3 ; median 756 pg/m 3 ). The highest level (median 1067 pg/m 3 ) was found at one of the urban sites in Beijing, followed by Tianjin (746 pg/m 3 ) and Shijiazhuang (724 pg/m 3 ). Tris(2-chloroethyl) phosphate (TCEP) and tri[(2R)-1-chloro-2-propyl] phosphate (TCPP) were the dominant compounds across the five sampling locations. Generally, the concentrations of chlorinated OPEs were relatively higher in summer than in winter (p < 0.05), but no significant seasonal difference was discovered for non-chlorinated individual OPEs. The concentrations of tri-n-butyl phosphate (TBP), TCEP, TCPP and triphenyl phosphate (TPP) were positively correlated with the meteorological parameters (i.e. temperature and relative humidity) (p < 0.05), indicating an evident influence of meteorological condition on OPE distribution. We observed a negative correlation (p < 0.05) between octanol-air partition coefficients (logK oa ) and the ratio of PM 2.5 -bound OPE concentrations to total suspended particulates-bound OPE concentrations, suggesting that physicochemical properties affect the particle-size distribution of OPEs. Furthermore, the median value of cancer hazard quotients (HQs) of TCEP was higher than TBP and tris(2-ethylhexyl) phosphate (TEHP). The health risk assessment showed that HQ values for children were ~1.6 times higher than those for adults. Relatively higher health risk induced by PM 2.5 -bound OPEs via inhalation was found during severe hazy days than in clear days., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Nanosized magnetite is a highly toxic material due to its strong ability to generate reactive oxygen species in vivo, and the presence of magnetite NPs in the brain has been linked with aging and neurodegenerative diseases such as Alzheimer's disease. Recently, magnetite pollution nanoparticles (NPs) were found to be present in the human brain, heart, and blood, which raises great concerns about the health risks of airborne magnetite NPs. Here, we report the abundant presence and chemical multifingerprints (including high-resolution structural and elemental fingerprints) of magnetite NPs in the urban atmosphere. We establish a methodology for high-efficiency retrieving and accurate quantification of airborne magnetite NPs. We report the occurrence levels (annual mean concentration 75.5 ± 33.2 ng m -3 in Beijing with clear season variations) and the pollution characteristics of airborne magnetite NPs. Based on the chemical multifingerprints of the NPs, we identify and estimate the contributions of the major emission sources for airborne magnetite NPs. We also give an assessment of human exposure risks of airborne magnetite NPs. Our findings support the identification of airborne magnetite NPs as a threat to human health.

Indoor exposure to legacy and novel brominated flame retardants (NBFRs) may cause potential risks to human health. Studies on seasonal variations of indoor PM 2.5 -bound BFRs are scant. This study comprehensively investigated the seasonal variations of PM 2.5 -bound polybrominated diphenyl ethers (PBDEs) and NBFRs in various indoor environments (i.e. activity room, dormitory, home and office) and outdoor PM 2.5 in Beijing, China over one year. The levels of PBDE (226 ± 108 pg m -3 ) were higher than that of NBFRs (27.0 ± 16.0 pg m -3 ) in all indoor environments. Decabromodiphenyl ether (BDE-209) and decabromodiphenyl ethane (DBDPE) were the most abundant BFRs. Office showed the highest mean concentrations of Σ 15 PBDEs (251 ± 125 pg m -3 ) and Σ 9 NBFRs (33.0 ± 18.0 pg m -3 ), which may be related to the higher number density of indoor materials. The concentrations of Σ 9 NBFRs and Σ 15 PBDE in indoor PM 2.5 were found to be significantly higher than those in the corresponding outdoor PM 2.5 (p < 0.05). Two to twenty-fold seasonal variations were observed for levels of PM 2.5 -bound BFRs during one year, and indoor concentrations increased slightly during the central-heating period (November 2016-March 2017). Seasonal variations of BFRs could be affected by temperature, relative humidity and concentrations of particle matters. The PM 2.5 -bound BFRs concentrations in PM 2.5 were negatively correlated with temperature and relative humidity, while positively correlated with PM 2.5 concentrations (p < 0.05). Atmospheric haze pollution could possibly contribute to higher levels of indoor PM 2.5 -bound BFRs. Human daily intake of BFRs via PM 2.5 inhalation showed seasonal differences, and the highest exposure risk occurred in winter. Toddlers were assessed to be more vulnerable to indoor PM 2.5 -bound BFRs in all seasons. This study provided the first-hand measurements of seasonal concentrations and human exposure to PM 2.5 -bound BFRs in different indoor scenarios in Beijing., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Peroxyacyl nitrates (PANs) are important secondary pollutants in ground-level atmosphere. Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation (BP) artificial neural network (ANN) and multiple linear regression (MLR) methods were used to predict the hourly average PAN concentrations at Peking University, Beijing, in 2014. The model inputs were atmospheric pollutant data and meteorological parameters. Model 3 using a BP-ANN based on the original variables achieved the best prediction results among the four models, with a correlation coefficient (R) of 0.7089, mean bias error of -0.0043 ppb, mean absolute error of 0.4836 ppb, root mean squared error of 0.5320 ppb, and Willmott's index of agreement of 0.8214. Based on a comparison of the performance indices of the MLR and BP-ANN models, we concluded that the BP-ANN model was able to capture the highly non-linear relationships between PAN concentration and the conventional atmospheric pollutant and meteorological parameters, providing more accurate results than the traditional MLR models did, with a markedly higher goodness of R. The selected meteorological and atmospheric pollutant parameters described a sufficient amount of PAN variation, and thus provided satisfactory prediction results. More specifically, the BP-ANN model performed very well for capturing the variation pattern when PAN concentrations were low. The findings of this study address some of the existing knowledge gaps in this research field and provide a theoretical basis for future regional air pollution control., (Copyright © 2018. Published by Elsevier B.V.)