中国严寒地区细颗粒物细菌群落特征研究
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摘要
通过对中国严寒地区典型城市大庆市供暖季3类建筑(办公室、教室、住宅)室内外共计110个测点长期监测,分析大庆市供暖季室内外细颗粒物关联性,并基于16S rDNA基因测序技术和BLAST源解析技术研究大庆市供暖季3类建筑室内外细颗粒物上细菌的组分及来源.研究结果表明:大庆市供暖季室内外PM_(2.5)平均质量浓度分别为(32±22)和(45±34)μg/m~3.其中办公室的平均渗透系数处于较低的状态(0.2886),教室的渗透系数处于较高的状态(0.5702),农村住宅(0.6513)比城市住宅的渗透系数略大(0.6057).不同类型建筑室内细颗粒物中的细菌组分存在一定差异,室外细颗粒物中的细菌组分根据采样地点也存在不同,但整体上厚壁菌门(Firmicuts)、变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)和生氧光细菌(Oxyphotobacteria)是大庆市供暖季细颗粒物中的优势菌群. 3类建筑室内外细颗粒物细菌来源主要为土壤、水体、人体、腐败有机物和粪便,但不同建筑类型及采样区域的细菌来源比例具有一定差异性.室内较室外人体来源所占比重大,而室外较室内土壤来源比重大.
Through the long-term monitoring of indoor and outdoor fine particles of 3 building types(office, classroom and residence) for 110 samples in heating season of Daqing, a typical city in cold region of China, it analyzed the relationship between indoor and outdoor fine particles during heating season. Using 16 S rDNA gene analysis method and BLAST source apportionment, the components and sources of bacterial communities in fine particles of 3 building types indoors and outdoors were studied. The results showed that average mass concentrations of indoor and outdoor PM_(2.5) in Daqing were(32±22) and(45±34)μg/m~3, respectively during heating season. The average permeability coefficient of office was lower(0.2886), classroom was higher(0.5702), and rural residence(0.6513) was larger than urban residence(0.6057) slightly. Firmicuts, Proteobacteria, Bacteroidetes and Oxyphotobacteria were the dominant bacterial phyla in fine particulate matter of Daqing during heating season on the whole. The sources for 3 building types of bacteria in fine particulate matter indoors and outdoors were mainly soil, water, human, corrupt organic and faeces, while different building types and sampling sites led to different source proportions of bacteria.
Through the long-term monitoring of indoor and outdoor fine particles of 3 building types(office, classroom and residence) for 110 samples in heating season of Daqing, a typical city in cold region of China, it analyzed the relationship between indoor and outdoor fine particles during heating season. Using 16 S rDNA gene analysis method and BLAST source apportionment, the components and sources of bacterial communities in fine particles of 3 building types indoors and outdoors were studied. The results showed that average mass concentrations of indoor and outdoor PM_(2.5) in Daqing were(32±22) and(45±34)μg/m~3, respectively during heating season. The average permeability coefficient of office was lower(0.2886), classroom was higher(0.5702), and rural residence(0.6513) was larger than urban residence(0.6057) slightly. Firmicuts, Proteobacteria, Bacteroidetes and Oxyphotobacteria were the dominant bacterial phyla in fine particulate matter of Daqing during heating season on the whole. The sources for 3 building types of bacteria in fine particulate matter indoors and outdoors were mainly soil, water, human, corrupt organic and faeces, while different building types and sampling sites led to different source proportions of bacteria.
引文
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[13]苟欢歌,鲁建江,李珊蔓,等.乌鲁木齐市冬季大气颗粒物中细菌群落结构研究[C].中国环境科学学会学术年会论文集, 2015:4835-4841.Gou H G, Lu J J, Li S M, et al. Study on the structure of bacterial community in atmospheric particulate matter in Urumqi in winter[C].Proceedings of the Annual meeting of the Chinese Society of Environmental Sciences, 2015:4835-4841.
[14] Bertolini V, Gandolfi I, Ambrosini R, et al. Tempotal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy[J].Applied microbiology and biotechnology, 2013,97(14):6561-6570.
[15] Zhou C, Zhu X, Wang Z, et al. Gas-particle partitioning of PAHs in the urban air of Dalian, China:measurements and assessments[J].Polycyclic Aromatic Compounds, 2013,33(1):31-51.
[16] MacNeill M, Wallace L, Kearney J, et al. Factors influencing variability in the infiltration of PM2.5 mass and its components[J].Atmospheric environment, 2012,61:518-532.
[17] Fan R, Wang D, Mao C, et al. Preliminary study of children's exposure to PAHs and its association with 8-hydroxy-2′-deoxyguanosine in Guangzhou, China[J]. Environment international, 2012,42:53-58.
[18]赖森潮,苏广宁,邹世春,等.广州市部分居室空气中PM2.5污染特征[J].环境与健康杂志, 2006,23(1):39-41.Lai S C, Su G N, Zou S C, et al. Characteristics of PM2.5 pollution in the air of some bedrooms in Guangzhou[J]. Journal of Environment and Health, 2006,23(1):39-41.
[19] Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads[J]. Embnet Journal, 2011,17(1).
[20] Edgar R C, Haas B J, Clemente J C, et al. UCHIME improves sensitivity and speed of chimera detection[J]. Bioinformatics, 2011,27(16):2194-2200.
[21] Haas B J, Gevers D, Earl A M, et al. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons[J]. Genome research, 2011,21(3):494-504.
[22] Edgar R C. UPARSE:highly accurate OTU sequences from microbial amplicon reads. Nature methods, 2013,10(10):996-998.
[23] Wang Q, Garrity G M, Tiedje J M, et al. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[J]. Applied and environmental microbiology, 2007,73(16):5261-5267.
[24] Quast C, Pruesse E, Yilmaz P, et al. The SILVA ribosomal RNA gene database project:improved data processing and web-based tools[J].Nucleic Acids Research, 2013,1(41):D590-D596.
[25] Edgar R C. MUSCLE:multiple sequence alignment with high accuracy and high flux. Nucleic Acids Research, 2004,32:1792–1797.
[26] Ott W, Wallace L, Mage D. Predicting particulate(PM10)personal exposure distributions using a random component superposition statistical model[J]. Journal of the air&waste management association, 2000,50(8):1390-1406.
[27] Hystad P U, Setton E M, Allen R W, et al. Modeling residential fine particulate matter infiltration for exposure assessment[J].Environmental Epidemiology, 2009,19(6):570-579.
[28] Barnp, Larson T, Noullett M, et al. Infiltration of forest fire and residential wood smoke:an evaluation of air cleaner effectiveness[J].Environmental Epidemiology, 2008,18(5):503-511.
[29]宋颖.西安市秋冬季微生物气溶胶中细菌群落结构特征研究[D].西安:长安大学, 2017.Song Y. Study on the characteristics of bacterial Community structure in microbial Aerosol in Xi'an in Autumn and Winter[D]. Xi'an:Changan University, 2017.
[30]姚文冲.基于高通量测序的南方典型旅游城市空气细菌群落特征研究[D].杭州:浙江工商大学, 2016.Yao W C. Study on characteristics of Air bacterial Community in typical tourist cities in South China based on High Flux sequencing[D]. Hangzhou:Zhejiang University of Industry and Commerce, 2016.
[31]张昊.典型城市颗粒物中微生物的群落结构及环境因素影响研究[D].杭州:浙江大学, 2018.Zhang H. Study on the Community structure and Environmental factors of microorganisms in typical Urban particulate matter[D].Hangzhou:Zhejiang University, 2018.
[32]廖旭,胡安谊,杨晓永,等.厦门冬季PM2.5颗粒物中细菌和真核微生物群落组成及其来源分析[J].生态环境学报, 2013,22(8):1395-1400.Liao X, Hu A Y,Yang X Y, et al. Composition and source analysis of bacteria and eukaryotes in winter PM2.5 particles in Xiamen[J].Journal of Ecological Environment, 2013,22(8):1395-1400.
[2] Dockery D W, Pope C A, Xu X P, et al. An association between air pollution and morality in six United-States cities[J]. New England Journal of Medicine, 1993,329(24):753-759.
[3] Dockery D W, Spengler J D. Indoor-outdoor relationships of respirable sulfates and particles[J]. Atmospheric Environment, 1981,15(3):335-343.
[4] Koutrakis P, Briggs S L K, Leaderer B P. Source apportionment of indoor aerosols in Suffolk and Onondaga Counties, New York[J].Environmental Science&Technology, 1992,26(3):521-527.
[5] Ozkaynak H, Xue J, Spengler J, et al. Personal exposure to airborne particles and metals:results from the Particle TEAM study in Riverside, California[J]. Journal of Exposure Analysis and Environmental Epidemiology, 1995,6(1):57-78.
[6]熊志明,张国强,彭建国,等.室内可吸入颗粒物污染研究现状[J].暖通空调, 2004,34(4):32-36.Xiong Z M, Zhang G Q, Peng J G, et al. Research status of indoor inhalable particulate pollution[J]. HVAC, 2004,34(4):32-36.
[7]霍奇森,江桂斌,汪海林,等.现代毒理学[M].北京:科学出版社,2011.Huo Q S, Jiang G B, Wang H L, et al. Modern toxicology[M]. Beijing:science Press, 2011.
[8]陶燕,羊德容,兰岚,等.兰州市空气污染对呼吸系统疾病入院人数的影响[J].中国环境科学, 2013,33(1):175-180.Tao Y, Yang D R, Lan L, et al. Effect of air pollution on hospitalization of respiratory diseases in Lanzhou[J]. China Environmental Science,2013,33(1):175
[9] Cao C, Jiang W, Wang B, et al. Inhalable Microorganisms in Beijing's PM2.5 and PM10 Pollutants during a Severe Smog Event[J].environmental science&technology, 2014,48(3):1499-1507
[10]郑云昊,李菁,要茂盛,等.生物气溶胶的昨天、今天和明天[J].科学通报, 2018,63(10):878-894.Zheng Y H, Li J, Yao M S, et al. Biological aerosols yesterday, today and tomorrow[J]. Scientific Bulletin, 2018,63(10):878-894.
[11] Cao C, Jiang W, wang B, et al. Inhalable microorganisms in Beijing's PM2.5 and PM10 pollutants during a severe smog event[J].Environmental Science&Technology, 2014,48(3):1499-1507.
[12]王步英,郎继东,张丽娜,等.基于16s rRNA基因测序法分析北京霾污染过程中PM2.5和PM10细菌群落特征[J].环境科学, 2015,36(8):2727-2734.Wang B Y, Lang J D, Zhang L N, et al. The characteristics of PM2.5and PM10 bacterial communities in the process of haze pollution in Beijing were analyzed by 16s rRNA gene sequencing[J].Environmental Science, 2015,36(8):2727-2734.
[13]苟欢歌,鲁建江,李珊蔓,等.乌鲁木齐市冬季大气颗粒物中细菌群落结构研究[C].中国环境科学学会学术年会论文集, 2015:4835-4841.Gou H G, Lu J J, Li S M, et al. Study on the structure of bacterial community in atmospheric particulate matter in Urumqi in winter[C].Proceedings of the Annual meeting of the Chinese Society of Environmental Sciences, 2015:4835-4841.
[14] Bertolini V, Gandolfi I, Ambrosini R, et al. Tempotal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy[J].Applied microbiology and biotechnology, 2013,97(14):6561-6570.
[15] Zhou C, Zhu X, Wang Z, et al. Gas-particle partitioning of PAHs in the urban air of Dalian, China:measurements and assessments[J].Polycyclic Aromatic Compounds, 2013,33(1):31-51.
[16] MacNeill M, Wallace L, Kearney J, et al. Factors influencing variability in the infiltration of PM2.5 mass and its components[J].Atmospheric environment, 2012,61:518-532.
[17] Fan R, Wang D, Mao C, et al. Preliminary study of children's exposure to PAHs and its association with 8-hydroxy-2′-deoxyguanosine in Guangzhou, China[J]. Environment international, 2012,42:53-58.
[18]赖森潮,苏广宁,邹世春,等.广州市部分居室空气中PM2.5污染特征[J].环境与健康杂志, 2006,23(1):39-41.Lai S C, Su G N, Zou S C, et al. Characteristics of PM2.5 pollution in the air of some bedrooms in Guangzhou[J]. Journal of Environment and Health, 2006,23(1):39-41.
[19] Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads[J]. Embnet Journal, 2011,17(1).
[20] Edgar R C, Haas B J, Clemente J C, et al. UCHIME improves sensitivity and speed of chimera detection[J]. Bioinformatics, 2011,27(16):2194-2200.
[21] Haas B J, Gevers D, Earl A M, et al. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons[J]. Genome research, 2011,21(3):494-504.
[22] Edgar R C. UPARSE:highly accurate OTU sequences from microbial amplicon reads. Nature methods, 2013,10(10):996-998.
[23] Wang Q, Garrity G M, Tiedje J M, et al. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[J]. Applied and environmental microbiology, 2007,73(16):5261-5267.
[24] Quast C, Pruesse E, Yilmaz P, et al. The SILVA ribosomal RNA gene database project:improved data processing and web-based tools[J].Nucleic Acids Research, 2013,1(41):D590-D596.
[25] Edgar R C. MUSCLE:multiple sequence alignment with high accuracy and high flux. Nucleic Acids Research, 2004,32:1792–1797.
[26] Ott W, Wallace L, Mage D. Predicting particulate(PM10)personal exposure distributions using a random component superposition statistical model[J]. Journal of the air&waste management association, 2000,50(8):1390-1406.
[27] Hystad P U, Setton E M, Allen R W, et al. Modeling residential fine particulate matter infiltration for exposure assessment[J].Environmental Epidemiology, 2009,19(6):570-579.
[28] Barnp, Larson T, Noullett M, et al. Infiltration of forest fire and residential wood smoke:an evaluation of air cleaner effectiveness[J].Environmental Epidemiology, 2008,18(5):503-511.
[29]宋颖.西安市秋冬季微生物气溶胶中细菌群落结构特征研究[D].西安:长安大学, 2017.Song Y. Study on the characteristics of bacterial Community structure in microbial Aerosol in Xi'an in Autumn and Winter[D]. Xi'an:Changan University, 2017.
[30]姚文冲.基于高通量测序的南方典型旅游城市空气细菌群落特征研究[D].杭州:浙江工商大学, 2016.Yao W C. Study on characteristics of Air bacterial Community in typical tourist cities in South China based on High Flux sequencing[D]. Hangzhou:Zhejiang University of Industry and Commerce, 2016.
[31]张昊.典型城市颗粒物中微生物的群落结构及环境因素影响研究[D].杭州:浙江大学, 2018.Zhang H. Study on the Community structure and Environmental factors of microorganisms in typical Urban particulate matter[D].Hangzhou:Zhejiang University, 2018.
[32]廖旭,胡安谊,杨晓永,等.厦门冬季PM2.5颗粒物中细菌和真核微生物群落组成及其来源分析[J].生态环境学报, 2013,22(8):1395-1400.Liao X, Hu A Y,Yang X Y, et al. Composition and source analysis of bacteria and eukaryotes in winter PM2.5 particles in Xiamen[J].Journal of Ecological Environment, 2013,22(8):1395-1400.
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