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Biological particles, as a fraction of organic particles, potentially play a crucial role in ice nucleation processes. However, the contributions and relationships of biological components and organic matter (OM) to atmospheric ice nucleation remain largely unexplored. Here, total ice nucleating particles (INPs), heat‐resistant INPs, lysozyme‐resistant INPs, nanoscale INPs (<0.22 μm), and heat‐resistant nanoscale INPs in precipitation collected at the summit of Mt. Lu, China, were determined using droplet freezing assays coupled with corresponding pretreatments. Heat‐sensitive INPs and lysozyme‐sensitive INPs were considered as biological INPs and bacterial INPs, respectively. Microorganisms and OM molecules in precipitation were identified by high‐throughput sequencing technology and ultrahigh‐resolution mass spectrometry, respectively. Results revealed a predominant biological (heat‐sensitive) composition (78.8% and 93.2%) of total and nanoscale INPs at temperatures above −15°C. Specifically, bacterial (lysozyme‐sensitive) INPs accounted for 36.1% of the biological INPs at temperatures above −15°C. A notable correlation between sulfur‐containing organic compounds, mainly proteinaceous and lignin‐like substances, and INPs was uncovered, with a co‐occurrence network linking these compounds to Gram‐positive bacteria and Agaricomycetes. This study underscored the possible significance of sulfur‐containing organic compounds in the ice nucleation capacity of biological INPs, further shedding light on the ice nucleation mechanisms and potential sources of biological INPs. Plain Language Summary: Ice nucleating particles (INPs) are particles that facilitate the freezing of water at temperatures above the homogenous freezing point, impacting cloud formation and precipitation processes in the atmosphere. This study identified different types of INPs, microbes, and organic matter in precipitation sampled from Mt. Lu in southeastern China and investigated the connections among them. The findings suggested that a significant portion of INPs were of biological origin. Sulfur‐containing organic compounds likely played an important role in ice nucleation, which may originate from certain microbial taxa. This study helps us understand the role of microbes and organic molecules in ice formation, which has broader implications in areas such as preserving biological materials at low temperatures or facilitating artificial snow production. Key Points: Biological materials predominated among the ice nucleating particles (INPs) identified in precipitationSulfur‐containing organic compounds, associated with specific microbial taxa, likely acted as efficient INPs in precipitationThis study provides a preliminary understanding of the connections among INPs, organic matter, and microorganisms [ABSTRACT FROM AUTHOR]

Environmental context: Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Rationale: The North China Plain (NCP) has been identified as an NH3 emission hotspot. Source apportionment of NH3 is a prerequisite for controlling NH3 or NH4+ pollution. Nitrogen stable isotope (δ 15N) analysis is a promising method for NH3 source apportionment but its accuracy is still in question. Methodology: In this study, daytime and nighttime PM2.5 samples were collected from two sites in Tianjin, NCP, in autumn. Concentrations and δ 15N of particulate NH4+ were then measured. Nitrogen stable isotope analyses and isotope mixing model (MixSIAR), and an atmospheric chemistry model (WRF-CMAQ-ISAM) were used to estimate the sources of NH3 in Tianjin. Results: Results from the MixSIAR and WRF-CMAQ-ISAM models suggested that all the sources including livestock breeding, N-fertiliser application, fossil fuels, NH3 slip (especially from traffic), human waste and biomass burning (mostly from bioapplication) were non-negligible to NH3 and NH4+ in Tianjin. This high complexity is due to significant agricultural and industrial production and residential life in Tianjin and the surrounding regions. Our results indicate all NH3 sources need to be considered if we want to reduce NH4+ pollution in Tianjin in autumn. Environmental context. Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Photograph by Libin Wu. This article belongs to the collection Dedication to Roy Harrison. [ABSTRACT FROM AUTHOR]

Objective: To investigate 38 Y-chromosome short tandem repeat (Y-STR) genetic polymorphisms in Beijing Han and analyze the genetic distance with neighboring or linguistically similar populations. Materials and Methods: In the study, we selected 531 unrelated male individuals of Beijing Han, and the results were statistically analyzed by testing with GSTAR™ 41Y reagents. Results: The allele peak heights were balanced among the Y loci, the amplified fragment ranged from 100 to 500 bps. A total of 531 haplotypes were detected in 531 samples. Eight null genotypes were observed on locus DYS448. One and three double alleles were observed on single-copy locus DYS576 and DYS19, respectively. DYS385 a/b, DYF387S1 a/b, and DYS527 a/b were more common in double copies, but 3, 13, and 11 triple alleles were detected, respectively. The gene diversity values of Y-STRs except DYS391, DYS438, and DYS645 were >0.5. Twenty-seven Y-STRs of Beijing Han population were selected for genetic distance comparison with 17 populations including Changchun Han, with Rst values ranging from 0.0002 to 0.1703. Conclusion: The 38 Y-STRs in this study have strong male lineage identification ability and have great potential for individual identification, kinship identification, Y-STR database construction, and genetic relationship research. [ABSTRACT FROM AUTHOR]

Secondary organic aerosols (SOAs) play a key role in climate change and public health. However, the oxidation state and volatility of SOAs are still not well understood. Here, we investigated the highly oxygenated organic molecules (HOMs) in SOAs formed from ozonolysis of β -pinene and limonene. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to characterize HOMs in aerosol filter samples, and a scanning mobility particle sizer (SMPS) was used to measure the concentration and size distribution of SOA particles. The relative abundance of HOMs (i.e., ratio of summed mass spectrometry peak intensity of HOMs to totally identified organic compounds) in limonene SOA was 14 %–20 %, higher than in β -pinene SOA (3 %–13 %), exhibiting different trends with increasing ozone concentrations. β -pinene oxidation-derived HOMs exhibit higher yield at high ozone concentration, accompanied by substantial formation of ultra-low-volatile organic compounds (ULVOCs). Limonene oxidation-derived HOMs exhibit higher yield at moderate ozone concentrations, with semi-, low-, and extremely low-volatile organic compounds (SVOCs, LOVCs, and ELVOCs) play a major role. Combined experimental evidence and theoretical analysis indicate that oxygen-increasing-based peroxy radical chemistry is a plausible mechanism for the formation of oxygenated organic compounds with 10 carbon atoms. Our findings show that HOMs and low-volatile species in β -pinene and limonene SOA are largely different. The ozone concentration-driven SOA formation and evolution mechanism for monoterpenes is suggested to be considered in future climate or exposure risk models, which may enable more accurate air quality prediction and management. [ABSTRACT FROM AUTHOR]