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Reviews in Environmental Science and Bio/Technology

, Volume 18, Issue 3, pp 495–523 | Cite as

Linking the conventional and emerging detection techniques for ambient bioaerosols: a review

  • Prakriti Sharma Ghimire
  • Lekhendra Tripathee
  • Pengfei Chen
  • Shichang KangEmail author
Review Paper

Abstract

Bioaerosols are biologically originated particles present in the atmosphere that can be formed from any process involving biological materials. They comprise of both living and non-living components including organisms, dispersal methods of organisms, and excretions. Bioaerosols such as airborne bacteria, fungal spores, pollen, and others possess diverse characteristics and effects. A large gap exists in the scientific understanding of the overall physical characteristics and measurement of bioaerosols. Consequently, this review aims to devise an appropriate approach to generate more scientific knowledge of bioaerosols. In addition to comparisons and discussions about the various factors affecting bioaerosols, sampling, handling, and the application of various devised analytical techniques, this review offers insight into the current state of bioaerosol research. The review focuses on instrumental and methodical strategies to understand bioaerosol measurement. Numerous studies have investigated conventional methods, advanced methods, and real-time methods that can be applied for bioaerosol monitoring. Each method is different in terms of working principle, characteristics, sensitivity, and efficiency. For the first time, this review explains and compares different methods of conventional, offline, online, and real-time detection methods of bioaerosols based on their working principles, sensitivity, and efficiency on a single platform. This will provide a clear concept and better options for selecting the appropriate method based on the research proposal. Furthermore, recent advances are summarized, and future outlooks are emphasized for bioaerosol identification and categorization. This study also encourages developing affordable and standardized methods to avoid the inter-laboratory and sampling variability to obtain a better understanding and comparison of bioaerosol measurements worldwide. Nevertheless, this work can assist researchers in selecting appropriate methods for bioaerosol measurement and investigation.

Keywords

Bioaerosol Atmosphere Bacteria Fungi Bioaerosol measurement Analytical approach 

Notes

Acknowledgements

We acknowledge the support provided by the National Natural Science Foundation of China (41630754, 41721091) and the State Key Laboratory of Cryospheric Science (SKLCS-ZZ-2018). Prakriti Sharma Ghimire is supported by a PIFI Fellowship from the Chinese Academy of Sciences (PIFI2018PC20021). Lekhendra Tripathee acknowledges the Chinese Academy of Science for international Young staff support under PIFI (2020FYC0001) program.

References

  1. Agranovski V, Ristovski Z, Hargreaves M, Blackall PJ, Morawska L (2003) Real-time measurement of bacterial aerosols with the UVAPS: performance evaluation. J Aerosol Sci 34(3):301–317Google Scholar
  2. Ali, S., 2010. Optical Processes in Microparticles and Nanostructures: A Festschrift Dedicated to Richard Kounai Chang on His Retirement from Yale University, 6. World ScientificGoogle Scholar
  3. Amann RI, Ludwig W, Schleifer K-H (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 59(1):143–169Google Scholar
  4. Amato P et al (2007) An important oceanic source of micro-organisms for cloud water at the Puy de Dôme (France). Atmos Environ 41(37):8253–8263Google Scholar
  5. Arslan D, Legendre M, Seltzer V, Abergel C, Claverie J-M (2011) Distant Mimivirus relative with a larger genome highlights the fundamental features of Megaviridae. Proc Natl Acad Sci 108(42):17486–17491Google Scholar
  6. Bauer H et al (2002) The contribution of bacteria and fungal spores to the organic carbon content of cloud water, precipitation and aerosols. Atmos Res 64(1–4):109–119Google Scholar
  7. Bowers RM et al (2009) Characterization of airborne microbial communities at a high-elevation site and their potential to act as atmospheric ice nuclei. Appl Environ Microbiol 75(15):5121–5130Google Scholar
  8. Bowers RM et al (2013) Seasonal variability in bacterial and fungal diversity of the near-surface atmosphere. Environ Sci Technol 47(21):12097–12106Google Scholar
  9. Bowley HJ, Gerrard DL, Louden JD, Turrell G (2012) Practical raman spectroscopy. Springer, BerlinGoogle Scholar
  10. Brągoszewska E, Mainka A, Pastuszka JS (2017) Concentration and size distribution of culturable bacteria in ambient air during spring and winter in Gliwice: a typical urban area. Atmosphere 8(12):239Google Scholar
  11. Bridge P, Spooner B (2001) Soil fungi: diversity and detection. Plant Soil 232(1–2):147–154Google Scholar
  12. Brosseau LM et al (2000) Differences in detected fluorescence among several bacterial species measured with a direct-reading particle sizer and fluorescence detector. Aerosol Sci Technol 32(6):545–558Google Scholar
  13. Burge HA (1995) Bioaerosol investigations. Bioaerosols. Lewis Publishers, Boca Raton, pp 1–23Google Scholar
  14. Cabredo S, Parra A, Saenz C, Anzano J (2009) Bioaerosols chemometric characterization by laser-induced fluorescence: air sample analysis. Talanta 77(5):1837–1842Google Scholar
  15. Castillo JA, Staton SJ, Taylor TJ, Herckes P, Hayes MA (2012) Exploring the feasibility of bioaerosol analysis as a novel fingerprinting technique. Anal Bioanal Chem 403(1):15–26Google Scholar
  16. Chen P-S, Li C-S (2005) Sampling performance for bioaerosols by flow cytometry with fluorochrome. Aerosol Sci Technol 39(3):231–237Google Scholar
  17. Chen P-S, Li C-S (2007) Real-time monitoring for bioaerosols—flow cytometry. Analyst 132(1):14–16Google Scholar
  18. Chi M-C, Li C-S (2007) Fluorochrome in monitoring atmospheric bioaerosols and correlations with meteorological factors and air pollutants. Aerosol Sci Technol 41(7):672–678Google Scholar
  19. Choi J, Kang M, Jung JH (2015) Integrated micro-optofluidic platform for real-time detection of airborne microorganisms. Sci Rep 5:15983Google Scholar
  20. Chow JC et al (2015) Characterization of ambient PM10 bioaerosols in a California agricultural town. Aerosol Air Qual Res 15(4):1433–1447Google Scholar
  21. Clauß M (2015) Particle size distribution of airborne microorganisms in the environment-a review. Appl Agric Forestry ResGoogle Scholar
  22. Corzo CA et al (2013) Relationship between airborne detection of influenza A virus and the number of infected pigs. Vet J 196(2):171–175Google Scholar
  23. Cox CS, Wathes CM (1995) Bioaerosols handbook. CRC Press, Boca RatonGoogle Scholar
  24. Crook B, Lacey J (1988) Enumeration of airborne micro-organisms in work environments. Environ Technol 9(6):515–520Google Scholar
  25. Damit B (2017) Droplet-based microfluidics detector for bioaerosol detection. Aerosol Sci Technol 51(4):488–500Google Scholar
  26. Darwin C (1846) An account of the fine dust which often falls on vessels in the Atlantic Ocean. Q J Geol Soc 2(1–2):26–30Google Scholar
  27. Dasgupta PK, Poruthoor SK (2002) Automated measurement of atmospheric particle composition, comprehensive analytical chemistry. Elsevier, Amsterdam, pp 161–218Google Scholar
  28. Deacon L et al (2009) Particle size distribution of airborne Aspergillus fumigatus spores emitted from compost using membrane filtration. Atmos Environ 43(35):5698–5701Google Scholar
  29. DeFreez R (2009) LIF bio-aerosol threat triggers: then and now, optically based biological and chemical detection for defence V. International Society for Optics and Photonics, pp 74840HGoogle Scholar
  30. Deguillaume L et al (2008) Microbiology and atmospheric processes: chemical interactions of primary biological aerosols. Biogeosci Discuss 5(1):841–870Google Scholar
  31. Després V et al (2007) Characterization of primary biogenic aerosol particles in urban, rural, and high-alpine air by DNA sequence and restriction fragment analysis of ribosomal RNA genes. Biogeosciences 4(6):1127–1141Google Scholar
  32. Després V et al (2012) Primary biological aerosol particles in the atmosphere: a review. Tellus B Chem Phys Meteorol 64(1):15598Google Scholar
  33. Douwes J et al (1999) Fungal extracellular polysaccharides in house dust as a marker for exposure to fungi: relations with culturable fungi, reported home dampness, and respiratory symptoms. J Allergy Clin Immunol 103(3):494–500Google Scholar
  34. Duchaine C et al (2001) Comparison of endotoxin exposure assessment by bioaerosol impinger and filter-sampling methods. Appl Environ Microbiol 67(6):2775–2780Google Scholar
  35. Dungan RS, Leytem AB (2009) Qualitative and quantitative methodologies for determination of airborne microorganisms at concentrated animal-feeding operations. World J Microbiol Biotechnol 25(9):1505–1518Google Scholar
  36. Dybwad M, Skogan G, Blatny JM (2014) Comparative testing and evaluation of nine different air samplers: end-to-end sampling efficiencies as specific performance measurements for bioaerosol applications. Aerosol Sci Technol 48(3):282–295Google Scholar
  37. Elbert W, Taylor P, Andreae M, Pöschl U (2007) Contribution of fungi to primary biogenic aerosols in the atmosphere: wet and dry discharged spores, carbohydrates, and inorganic ions. Atmos Chem Phys 7(17):4569–4588Google Scholar
  38. Engelhart S, Glasmacher A, Simon A, Exner M (2007) Air sampling of Aspergillus fumigatus and other thermotolerant fungi: comparative performance of the Sartorius MD8 airport and the Merck MAS-100 portable bioaerosol sampler. Int J Hyg Environ Health 210(6):733–739Google Scholar
  39. Estillore AD, Trueblood JV, Grassian VH (2016) Atmospheric chemistry of bioaerosols: heterogeneous and multiphase reactions with atmospheric oxidants and other trace gases. Chem Science 7(11):6604–6616Google Scholar
  40. Evanoff DD, Heckel J, Caldwell TP, Christensen KA, Chumanov G (2006) Monitoring DPA release from a single germinating bacillus s ubtilis endospore via surface-enhanced Raman Scattering Microscopy. J Am Chem Soc 128(39):12618–12619Google Scholar
  41. Eversole JD, Roselle D, Seaver ME (1999) Monitoring biological aerosols using UV fluorescence, Air Monitoring and Detection of Chemical and Biological Agents. International Society for Optics and Photonics, pp 34–43Google Scholar
  42. Eversole J et al (2001) Continuous bioaerosol monitoring using UV excitation fluorescence: outdoor test results. Field Anal Chem Technol 5(4):205–212Google Scholar
  43. Fabian M, Miller S, Reponen T, Hernandez M (2005) Ambient bioaerosol indices for indoor air quality assessments of flood reclamation. J Aerosol Sci 36(5–6):763–783Google Scholar
  44. Fabian P, McDevitt J, Houseman E, Milton D (2009) Airborne influenza virus detection with four aerosol samplers using molecular and infectivity assays: considerations for a new infectious virus aerosol sampler. J Aerosol Sci 19(5):433–441Google Scholar
  45. Falacy JS (2003) Detection of Erysiphe necator (Uncinula necator) with polymerase chain reaction and species-specific primersGoogle Scholar
  46. Fannin K (1981) An approach to the study of environmental microbial aerosols, Water Pollution Research and Development. Elsevier, pp 1103–1119Google Scholar
  47. Fennelly M, Sewell G, Prentice M, O’Connor D, Sodeau J (2017) The use of real-time fluorescence instrumentation to monitor ambient primary biological aerosol particles (PBAP). Atmosphere 9(1):1Google Scholar
  48. Fergenson DP et al (2004) Reagentless detection and classification of individual bioaerosol particles in seconds. Anal Chem 76(2):373–378Google Scholar
  49. Frohlich-Nowoisky J, Pickersgill DA, Despres VR, Poschl U (2009) High diversity of fungi in air particulate matter. Proc Natl Acad Sci U S A 106(31):12814–12819Google Scholar
  50. Fröhlich-Nowoisky J et al (2016) Bioaerosols in the Earth system: climate, health, and ecosystem interactions. Atmos Res 182:346–376Google Scholar
  51. Gabey A et al (2010) Measurements and comparison of primary biological aerosol above and below a tropical forest canopy using a dual channel fluorescence spectrometer. Atmos Chem Phys 10(10):4453–4466Google Scholar
  52. Gabey A, Stanley W, Gallagher M, Kaye PH (2011) The fluorescence properties of aerosol larger than 0.8 μm in urban and tropical rainforest locations. Atmos Chem Phys 11(11):5491–5504Google Scholar
  53. Gard E et al (1997) Real-time analysis of individual atmospheric aerosol particles: design and performance of a portable ATOFMS. Anal Chem 69(20):4083–4091Google Scholar
  54. Genic Staphylococci P (2004) Phylogenetic considerations. Clin Microbiol Rev 17(2):840–862Google Scholar
  55. Gentry JW (1997) The legacy of John Tyndall in aerosol science. J Aerosol Sci 28(8):1365–1372Google Scholar
  56. Georgakopoulos D et al (2009) Microbiology and atmospheric processes: biological, physical and chemical characterization of aerosol particles. Biogeosciences 6(4):721–737Google Scholar
  57. Ghosh B, Lal H, Srivastava A (2015) Review of bioaerosols in indoor environment with special reference to sampling, analysis and control mechanisms. Environ Int 85:254–272Google Scholar
  58. Gilbert Y, Duchaine C (2009) Bioaerosols in industrial environments: a review. Can J Civil Eng 36(12):1873–1886Google Scholar
  59. Globus T, Gelmont B (2014) Biological detection with terahertz spectroscopy, bioaerosol detection technologies. Springer, Berlin, pp 241–264Google Scholar
  60. Globus T et al (2003) THz-frequency spectroscopic sensing of DNA and related biological materials. Int J High Speed Electron Syst 13(04):903–936Google Scholar
  61. Globus T, Khromova T, Woolard D, Gelmont B (2004) Terahertz Fourier transform characterization of biological materials in solid and liquid phases, chemical and biological standoff detection. International Society for Optics and Photonics, pp 10–19Google Scholar
  62. Golding CG, Lamboo LL, Beniac DR, Booth TF (2016) The scanning electron microscope in microbiology and diagnosis of infectious disease. Sci Rep 6:26516Google Scholar
  63. Gosselin MI et al (2016) Fluorescent bioaerosol particle, molecular tracer, and fungal spore concentrations during dry and rainy periods in a semi-arid forest. Atmos Chem Phys 16(23):15165–15184Google Scholar
  64. Griffiths W, Boysan F (1996) Computational fluid dynamics (CFD) and empirical modelling of the performance of a number of cyclone samplers. J Aerosol Sci 27(2):281–304Google Scholar
  65. Griffiths W, Stewart I, Futter S, Upton S, Mark D (1997) The development of sampling methods for the assessment of indoor bioaerosols. J Aerosol Sci 28(3):437–457Google Scholar
  66. Gόrny RL, Dutkiewicz J, Krysinska-Traczyk E (1999) Size distribution of bacterial and fungal bioaerosols in indoor air. Ann Agric Environ Med 6:105–113Google Scholar
  67. Haddrell AE, Thomas RJ (2017) Aerobiology: experimental considerations, observations, and future tools. Appl Environ Microbiol 83(17)Google Scholar
  68. Hairston PP, Ho J, Quant FR (1997) Design of an instrument for real-time detection of bioaerosols using simultaneous measurement of particle aerodynamic size and intrinsic fluorescence. J Aerosol Sci 28(3):471–482Google Scholar
  69. Hall RJ et al (2013) Metagenomic detection of viruses in aerosol samples from workers in animal slaughterhouses. PLoS ONE 8(8):e72226Google Scholar
  70. Han T, Mainelis G (2008) Design and development of an electrostatic sampler for bioaerosols with high concentration rate. J Aerosol Sci 39(12):1066–1078Google Scholar
  71. Han T, An HR, Mainelis G (2010) Performance of an electrostatic precipitator with superhydrophobic surface when collecting airborne bacteria. Aerosol Sci Technol 44(5):339–348Google Scholar
  72. Han T, Wren M, DuBois K, Therkorn J, Mainelis G (2015) Application of ATP-based bioluminescence for bioaerosol quantification: effect of sampling method. J Aerosol Sci 90:114–123Google Scholar
  73. He Q, Yao M (2011) Integration of high volume portable aerosol-to-hydrosol sampling and qPCR in monitoring bioaerosols. J Environ Monit 13(3):706–712Google Scholar
  74. Healy D et al (2014) Ambient measurements of biological aerosol particles near Killarney, Ireland: a comparison between real-time fluorescence and microscopy techniques. Atmos Chem Phys 14(15):8055–8069Google Scholar
  75. Heidelberg J et al (1997) Effect of aerosolization on culturability and viability of gram-negative bacteria. Appl Environ Microbiol 63(9):3585–3588Google Scholar
  76. Heikkinen M, Hjelmoroos-Koski M, Haggblom M, Macher J (2005) Bioaerosols. In: LS Ruzer, NH Harley Aerosols handbook, measurement, dosimetry, and health effects. CRC Press, New YorkGoogle Scholar
  77. Henningson EW, Ahlberg MS (1994) Evaluation of microbiological aerosol samplers: a review. J Aerosol Sci 25(8):1459–1492Google Scholar
  78. Hernandez M et al. (2016) Chamber catalogues of optical and fluorescent signatures distinguish bioaerosol classes. Atmos Meas Tech 9(7)Google Scholar
  79. Hirst E, Kaye PH (1996) Experimental and theoretical light scattering profiles from spherical and nonspherical particles. J Geophys Res Atmos 101(D14):19231–19235Google Scholar
  80. Ho J (2011) Use of virtual impactor (VI) technology in biological aerosol detection. KONA Powder Part J 29:16–26Google Scholar
  81. Ho J, Spence M, Hairston P (1999) Measurement of biological aerosol with a fluorescent aerodynamic particle sizer (FLAPS): correlation of optical data with biological data. Aerobiologia 15(4):281–291Google Scholar
  82. Hogan C Jr et al (2005) Sampling methodologies and dosage assessment techniques for submicrometre and ultrafine virus aerosol particles. J Appl Microbiol 99(6):1422–1434Google Scholar
  83. Hoisington AJ, Maestre JP, King MD, Siegel JA, Kinney KA (2014) Impact of sampler selection on the characterization of the indoor microbiome via high-throughput sequencing. Build Environ 80:274–282Google Scholar
  84. Huffman J, Treutlein B, Pöschl U (2010) Fluorescent biological aerosol particle concentrations and size distributions measured with an ultraviolet aerodynamic particle sizer (UV-APS) in Central Europe. Atmos Chem Phys 10(7):3215–3233Google Scholar
  85. Huffman J et al (2012) Size distributions and temporal variations of biological aerosol particles in the Amazon rainforest characterized by microscopy and real-time UV-APS fluorescence techniques during AMAZE-08. Atmos Chem Phys 12(24):11997–12019Google Scholar
  86. Huffman JA et al (2013) High concentrations of biological aerosol particles and ice nuclei during and after rain. Atmos Chem Phys 13(13):6151Google Scholar
  87. Humbal C, Gautam S, Trivedi U (2018) A review on recent progress in observations, and health effects of bioaerosols. Environ Int 118:189–193Google Scholar
  88. Imai M et al (2012) Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets. Nature 486(7403):420Google Scholar
  89. Jaenicke R (2005) Abundance of cellular material and proteins in the atmosphere. Science 308(5718):73Google Scholar
  90. Jones LJ, Carballido-López R, Errington J (2001) Control of cell shape in bacteria: helical, actin-like filaments in Bacillus subtilis. Cell 104(6):913–922Google Scholar
  91. Jonsson P, Kullander F (2014) Bioaerosol detection with fluorescence spectroscopy, bioaerosol detection technologies. Springer, Berlin, pp 111–141Google Scholar
  92. Juozaitis A, Willeke K, Grinshpun SA, Donnelly J (1994) Impaction onto a glass slide or agar versus impingement into a liquid for the collection and recovery of airborne microorganisms. Appl Environ Microbiol 60(3):861–870Google Scholar
  93. Kamperman T, Trikalitis VD, Karperien M, Visser CW, Leijten J (2018) Ultrahigh-throughput production of monodisperse and multifunctional janus microparticles using in-air microfluidics. ACS Appl Mater Interfaces 10(28):23433–23438Google Scholar
  94. Karl DM (1980) Cellular nucleotide measurements and applications in microbial ecology. Microbiol Rev 44(4):739Google Scholar
  95. Kaye PH, Eyles N, Ludlow I, Clark J (1991) An instrument for the classification of airborne particles on the basis of size, shape, and count frequency. Atmos Environ Part A Gen Top 25(3–4):645–654Google Scholar
  96. Kaye PH, Alexander-Buckley K, Hirst E, Saunders S, Clark J (1996) A real-time monitoring system for airborne particle shape and size analysis. J Geophys Res Atmos 101(D14):19215–19221Google Scholar
  97. Kaye PH et al (2005) Single particle multichannel bio-aerosol fluorescence sensor. Opt Express 13(10):3583–3593Google Scholar
  98. Kesavan J, Hottell K (2005) Characteristics and sampling efficiencies of two bioguardian (Registered) 12.03 Aerosol samplers, Edgewood Chemical Biological Center, Aberdeen Proving Ground MDGoogle Scholar
  99. Kesavan J, Sagripanti J-L (2015) Evaluation criteria for bioaerosol samplers. Environ Sci Process Impacts 17(3):638–645Google Scholar
  100. Kesavan J, Schepers D, McFarland AR (2010) Sampling and retention efficiencies of batch-type liquid-based bioaerosol samplers. Aerosol Sci Technol 44(10):817–829Google Scholar
  101. Krafft C (2010) Raman and CARS microscopy of cells and tissues, handbook of photonics for biomedical science. CRC Press, Boca Raton, pp 229–259Google Scholar
  102. L’Orange C, Anderson K, Sleeth D, Anthony TR, Volckens J (2015) A simple and disposable sampler for inhalable aerosol. Ann Occup Hyg 60(2):150–160Google Scholar
  103. Lal H, Ghosh B, Srivastava A, Srivastava A (2017) Identification and characterization of size-segregated bioaerosols at different sites in Delhi. Aerosol Air Qual Res 17(6):1570–1581Google Scholar
  104. Lee BU (2011) Life comes from the air: a short review on bioaerosol control. Aerosol Air Qual Res 11(7):921–927Google Scholar
  105. Lee S-A et al (2004) Assessment of electrical charge on airborne microorganisms by a new bioaerosol sampling method. J Occup Environ Hyg 1(3):127–138Google Scholar
  106. Lee J, Jang J, Akin D, Savran CA, Bashir R (2008) Real-time detection of airborne viruses on a mass-sensitive device. Appl Phys Lett 93(1):013901Google Scholar
  107. Lee S, Choi B, Yi SM, Ko G (2009) Characterization of microbial community during Asian dust events in Korea. Sci Total Environ 407(20):5308–5314Google Scholar
  108. Lee SH et al (2010) Identification of airborne bacterial and fungal community structures in an urban area by T-RFLP analysis and quantitative real-time PCR. Sci Total Environ 408(6):1349–1357Google Scholar
  109. Li C-S (1999) Sampling performance of impactors for bacterial bioaerosols. Aerosol Sci Technol 30(3):280–287Google Scholar
  110. Li M, Xu J, Romero-Gonzalez M, Banwart SA, Huang WE (2012) Single cell Raman spectroscopy for cell sorting and imaging. Curr Opin Biotechnol 23(1):56–63Google Scholar
  111. Lim DV, Simpson JM, Kearns EA, Kramer MF (2005) Current and developing technologies for monitoring agents of bioterrorism and biowarfare. Clin Microbiol Rev 18(4):583–607Google Scholar
  112. Lin W-H (1999) Collection efficiency and culturability of impingement into a liquid for bioaerosols of fungal spores and yeast cells. Aerosol Sci Technol 30(2):109–118Google Scholar
  113. Lin X, Willeke K, Ulevicius V, Grinshpun SA (1997) Effect of sampling time on the collection efficiency of all-glass impingers. Am Ind Hyg Assoc J 58(7):480–488Google Scholar
  114. Lindsley WG, Schmechel D, Chen BT (2006) A two-stage cyclone using microcentrifuge tubes for personal bioaerosol sampling. J Environ Monit 8(11):1136–1142Google Scholar
  115. Löndahl J (2014) Physical and biological properties of bioaerosols. Bioaerosol Detection Technologies, Integrated Analytical Systems, pp 33–48Google Scholar
  116. Macher J (1999) Developing a sampling plan. Bioaerosols Assess Control 5:1–5Google Scholar
  117. Madsen AM, Zervas A, Tendal K, Nielsen JL (2015) Microbial diversity in bioaerosol samples causing ODTS compared to reference bioaerosol samples as measured using Illumina sequencing and MALDI-TOF. Environ Res 140:255–267Google Scholar
  118. Mainelis G (1999) Collection of airborne microorganisms by electrostatic precipitation. Aerosol Sci Technol 30(2):127–144Google Scholar
  119. Mainelis G, Tabayoyong M (2010) The effect of sampling time on the overall performance of portable microbial impactors. Aerosol Sci Technol 44(1):75–82Google Scholar
  120. Mainelis G et al (2001) Electrical charges on airborne microorganisms. J Aerosol Sci 32(9):1087–1110Google Scholar
  121. Maliutina K, Tahmasebi A, Yu J (2018) Effects of pressure on morphology and structure of bio-char from pressurized entrained-flow pyrolysis of microalgae. Data Brief 18:422–431Google Scholar
  122. McFarland AR et al (2010) Wetted wall cyclones for bioaerosol sampling. Aerosol Sci Technol 44(4):241–252Google Scholar
  123. Mehta SK, Mishra S, Pierson DL (1996) Evaluation of three portable samplers for monitoring airborne fungi. Appl Environ Microbiol 62(5):1835–1838Google Scholar
  124. Menetrez MY et al (2007) The measurement of ambient bioaerosol exposure. Aerosol Sci Technol 41(9):884–893Google Scholar
  125. Miaskiewicz-Peska E, Lebkowska M (2012) Comparison of aerosol and bioaerosol collection on air filters. Aerobiologia (Bologna) 28(2):185–193Google Scholar
  126. Moon H-S, Lee J-H, Kwon K, Jung H-I (2012) Review of recent progress in micro-systems for the detection and analysis of airborne microorganisms. Anal Lett 45(2–3):113–129Google Scholar
  127. Nasir Z et al (2018) A controlled study on the characterisation of bioaerosols emissions from compost. Atmosphere 9(10):379Google Scholar
  128. Nasir ZA et al (2019) Scoping studies to establish the capability and utility of a real-time bioaerosol sensor to characterise emissions from environmental sources. Sci Total Environ 648:25–32Google Scholar
  129. Nevalainen A, Pastuszka J, Liebhaber F, Willeke K (1992) Performance of bioaerosol samplers: collection characteristics and sampler design considerations. Atmos Environ Part A Gen Top 26(4):531–540Google Scholar
  130. Noble CA, Prather KA (2000) Real-time single particle mass spectrometry: a historical review of a quarter century of the chemical analysis of aerosols. Mass Spectrom Rev 19(4):248–274Google Scholar
  131. Nonnenmann M, Bextine B, Dowd S, Gilmore K, Levin J (2010) Culture-independent characterization of bacteria and fungi in a poultry bioaerosol using pyrosequencing: a new approach. J Occup Environ Hyg 7(12):693–699Google Scholar
  132. Noris F, Siegel JA, Kinney KA (2011) Evaluation of HVAC filters as a sampling mechanism for indoor microbial communities. Atmos Environ 45(2):338–346Google Scholar
  133. Núñez A et al (2016) Monitoring of airborne biological particles in outdoor atmosphere. Part 1: importance, variability and ratiosGoogle Scholar
  134. O’Connor DJ, Healy DA, Sodeau JR (2013) The on-line detection of biological particle emissions from selected agricultural materials using the WIBS-4 (Waveband Integrated Bioaerosol Sensor) technique. Atmos Environ 80:415–425Google Scholar
  135. Pan Y-L et al (2010) Fluorescence spectra of atmospheric aerosol particles measured using one or two excitation wavelengths: comparison of classification schemes employing different emission and scattering results. Opt Express 18(12):12436–12457Google Scholar
  136. Park J-W, Kim HR, Hwang J (2016) Continuous and real-time bioaerosol monitoring by combined aerosol-to-hydrosol sampling and ATP bioluminescence assay. Analy Chim Acta 941:101–107Google Scholar
  137. Pathak, A.K., 2014. RECENT TRENDS IN BIO-AEROSOL STUDIES. CIBTech Journal of Microbiology, 4(3)Google Scholar
  138. Phan HN, McFarland AR (2004) Aerosol-to-hydrosol transfer stages for use in bioaerosol sampling. Aerosol Sci Technol 38(4):300–310Google Scholar
  139. Pillai SD, Ricke SC (2002) Review/Synthèse Bioaerosols from municipal and animal wastes: background and contemporary issues. Can J Microbiol 48(8):681–696Google Scholar
  140. Polymenakou PN, Mandalakis M, Stephanou EG, Tselepides A (2007) Particle size distribution of airborne microorganisms and pathogens during an intense African dust event in the eastern Mediterranean. Environ Health Perspect 116(3):292–296Google Scholar
  141. Predicala BZ, Urban JE, Maghirang RG, Jerez SB, Goodband RD (2002) Assessment of bioaerosols in swine barns by filtration and impaction. Curr Microbiol 44(2):136–140Google Scholar
  142. Prussin AJ 2nd, Marr LC (2015) Sources of airborne microorganisms in the built environment. Microbiome 3:78Google Scholar
  143. Prussin AJ 2nd, Marr LC, Bibby KJ (2014) Challenges of studying viral aerosol metagenomics and communities in comparison with bacterial and fungal aerosols. FEMS Microbiol Lett 357(1):1–9Google Scholar
  144. Raisi L, Aleksandropoulou V, Lazaridis M, Katsivela E (2013) Size distribution of viable, cultivable, airborne microbes and their relationship to particulate matter concentrations and meteorological conditions in a Mediterranean site. Aerobiologia 29(2):233–248Google Scholar
  145. Rathnayake CM et al (2017) Influence of rain on the abundance of bioaerosols in fine and coarse particles. Atmos Chem Phys 17(3):2459–2475Google Scholar
  146. Reponen T, Hyvärinen A, Ruuskanen J, Raunemaa T, Nevalainen A (1994) Comparison of concentrations and size distributions of fungal spores in buildings with and without mould problems. J Aerosol Sci 25(8):1595–1603Google Scholar
  147. Reponen, T., Willeke, K., Grinshpun, S., Nevalainen, A., 2011. Biological particle sampling. Aerosol measurement: principles, techniques, and applications: 549-570Google Scholar
  148. Rinsoz T, Duquenne P, Greff-Mirguet G, Oppliger A (2008) Application of real-time PCR for total airborne bacterial assessment: comparison with epifluorescence microscopy and culture-dependent methods. Atmos Environ 42(28):6767–6774Google Scholar
  149. Robins A (2014) Blackett Review on wide-area biological detectionGoogle Scholar
  150. Roux J-M, Kaspari O, Heinrich R, Hanschmann N, Grunow R (2013) Investigation of a new electrostatic sampler for concentrating biological and non-biological aerosol particles. Aerosol Sci Technol 47(5):463–471Google Scholar
  151. Rule AM, Kesavan J, Schwab KJ, Buckley TJ (2007) Application of flow cytometry for the assessment of preservation and recovery efficiency of bioaerosol samplers spiked with Pantoea agglomerans. Enviro Sci Technol 41(7):2467–2472Google Scholar
  152. Russell SC et al (2004) Toward understanding the ionization of biomarkers from micrometer particles by bio-aerosol mass spectrometry. J Am Soc Mass Spectrom 15(6):900–909Google Scholar
  153. Ryškevič N et al (2010) Concept design of a UV light-emitting diode based fluorescence sensor for real-time bioparticle detection. Sensors Actuators B Chem 148(2):371–378Google Scholar
  154. Sahu A, Grimberg SJ, Holsen TM (2005) A static water surface sampler to measure bioaerosol deposition and characterize microbial community diversity. J Aerosol Sci 36(5–6):639–650Google Scholar
  155. Sengupta A, Laucks M, Dildine N, Drapala E, Davis E (2005a) Bioaerosol characterization by surface-enhanced Raman spectroscopy (SERS). J Aerosol Sci 36(5–6):651–664Google Scholar
  156. Sengupta A, Laucks ML, Davis EJ (2005b) Surface-enhanced Raman spectroscopy of bacteria and pollen. Appl Spectrosc 59(8):1016–1023Google Scholar
  157. Seshadri S, Han T, Krumins V, Fennell DE, Mainelis G (2009) Application of ATP bioluminescence method to characterize performance of bioaerosol sampling devices. J Aerosol Sci 40(2):113–121Google Scholar
  158. Sharma Ghimire P et al (2016) Insight into enzymatic degradation of corn, wheat, and soybean cell wall cellulose using quantitative secretome analysis of Aspergillus fumigatus. J Proteome Res 15(12):4387–4402Google Scholar
  159. Shintani H, Taniai E, Miki A, Kurosu S, Hayashi F (2004) Comparison of the collecting efficiency of microbiological air samplers. J Hosp Infect 56(1):42–48Google Scholar
  160. Sivaprakasam V, Huston AL, Scotto C, Eversole JD (2004) Multiple UV wavelength excitation and fluorescence of bioaerosols. Opt Express 12(19):4457–4466Google Scholar
  161. Smets W, Moretti S, Denys S, Lebeer S (2016) Airborne bacteria in the atmosphere: presence, purpose, and potential. Atmos Environ 139:214–221Google Scholar
  162. Stetzenbach LD (2007) Introduction to aerobiology, Manual of Environmental Microbiology, Third Edition. American Society of Microbiology, pp 925–938Google Scholar
  163. Suess DT, Prather KA (1999) Mass spectrometry of aerosols. Chem Rev 99(10):3007–3036Google Scholar
  164. Svensson T (2016) Airborne microorganisms. A methodology to examine viability of bioaerosols. http://lup.lub.lu.se/student-papers/record/8884293
  165. Szponar B, Larsson L (2001) Use of mass spectrometry for characterising microbial communities in bioaerosols. Ann Agric Environ Med 8(2):111–117Google Scholar
  166. Taiwo AM, Beddows DC, Shi Z, Harrison RM (2014) Mass and number size distributions of particulate matter components: comparison of an industrial site and an urban background site. Sci Total Environ 475:29–38Google Scholar
  167. Tan M, Shen F, Yao M, Zhu T (2011) Development of an automated electrostatic sampler (AES) for bioaerosol detection. Aerosol Sci Technol 45(9):1154–1160Google Scholar
  168. Tang, J.W., 2009. The effect of environmental parameters on the survival of airborne infectious agents. Journal of the Royal Society Interface: rsif20090227Google Scholar
  169. Taylor PE, Flagan RC, Valenta R, Glovsky MM (2002) Release of allergens as respirable aerosols: a link between grass pollen and asthma. J Allergy Clin Immunol 109(1):51–56Google Scholar
  170. Terzieva S et al (1996) Comparison of methods for detection and enumeration of airborne microorganisms collected by liquid impingement. Appl Environ Microbiol 62(7):2264–2272Google Scholar
  171. Thompson MW, Donnelly J, Grinshpun SA, Juozaitis A, Willeke K (1994) Method and test system for evaluation of bioaerosol samplers. J Aerosol Sci 25(8):1579–1593Google Scholar
  172. Tobias HJ et al (2005) Bioaerosol mass spectrometry for rapid detection of individual airborne Mycobacterium tuberculosis H37Ra particles. Appl Environ Microbiol 71(10):6086–6095Google Scholar
  173. Tripathi A et al (2009) Bioaerosol analysis with Raman chemical imaging microspectroscopy. Anal Chem 81(16):6981–6990Google Scholar
  174. Trunov M, Trakumas S, Willeke K, Grinshpun SA, Reponen T (2001) Collection of bioaerosol particles by impaction: effect of fungal spore agglomeration and bounce. Aerosol Sci Technol 35(1):617–624Google Scholar
  175. Tseng C-C, Li C-S (2005) Collection efficiencies of aerosol samplers for virus-containing aerosols. J Aerosol Sci 36(5–6):593–607Google Scholar
  176. Unterwurzacher V et al (2018) Validation of a quantitative PCR based detection system for indoor mold exposure assessment in bioaerosols. Environmental Science: Processes & ImpactsGoogle Scholar
  177. Van Duyne RP (1979) Laser excitation of Raman scattering from adsorbed molecules on electrode surfaces. Chem Biochem Appl Lasers 4:101Google Scholar
  178. Van Wuijckhuijse A et al (2005) Matrix-assisted laser desorption/ionisation aerosol time-of-flight mass spectrometry for the analysis of bioaerosols: development of a fast detector for airborne biological pathogens. J Aerosol Sci 36(5–6):677–687Google Scholar
  179. Vanhee LM, Nelis HJ, Coenye T (2009) Detection and quantification of viable airborne bacteria and fungi using solid-phase cytometry. Nat Protoc 4(2):224–231Google Scholar
  180. Verboket PE, Borovinskaya O, Meyer N, Günther D, Dittrich PS (2014) A new microfluidics-based droplet dispenser for ICPMS. Anal Chem 86(12):6012–6018Google Scholar
  181. Verreault D, Moineau S, Duchaine C (2008) Methods for sampling of airborne viruses. Microbiol Mol Biol Rev 72(3):413–444Google Scholar
  182. Wang Z, Reponen T, Grinshpun SA, Górny RL, Willeke K (2001) Effect of sampling time and air humidity on the bioefficiency of filter samplers for bioaerosol collection. J Aerosol Sci 32(5):661–674Google Scholar
  183. Wang CH et al (2015) Field evaluation of personal sampling methods for multiple bioaerosols. PLoS ONE 10(3):e0120308Google Scholar
  184. Welker M, Moore ER (2011) Applications of whole-cell matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry in systematic microbiology. Syst Appl Microbiol 34(1):2–11Google Scholar
  185. Willeke K, Lin X, Grinshpun SA (1998) Improved aerosol collection by combined impaction and centrifugal motion. Aerosol Sci Technol 28(5):439–456Google Scholar
  186. Woodward RM (2004) Terahertz technology in biological and chemical sensing for defence, Optically Based Biological and Chemical Sensing for Defence. International Society for Optics and Photonics, pp. 341–353Google Scholar
  187. Wu Y et al (2015) MS2 virus inactivation by atmospheric-pressure cold plasma using different gas carriers and power levels. Appl Environ Microbiol 81(3):996–1002Google Scholar
  188. Xu Z, Yao M (2011) Analysis of culturable bacterial and fungal aerosol diversity obtained using different samplers and culturing methods. Aerosol Sci Technol 45(9):1143–1153Google Scholar
  189. Xu Z et al (2011) Bioaerosol science, technology, and engineering: past, present, and future. Aerosol Sci Technol 45(11):1337–1349Google Scholar
  190. Yamamoto N, Nazaroff WW, Peccia J (2014) Assessing the aerodynamic diameters of taxon-specific fungal bioaerosols by quantitative PCR and next-generation DNA sequencing. J Aerosol Sci 78:1–10Google Scholar
  191. Yao M (2018) Reprint of bioaerosol: a bridge and opportunity for many scientific research fields. J Aerosol Sci 119:91–96Google Scholar
  192. Yao M, Mainelis G (2006) Utilization of natural electrical charges on airborne microorganisms for their collection by electrostatic means. J Aerosol Sci 37(4):513–527Google Scholar
  193. Yao M, Mainelis G (2007) Analysis of portable impactor performance for enumeration of viable bioaerosols. J Occup Environ Hyg 4(7):514–524Google Scholar
  194. Yoo K, Yoo H, Lee JM, Shukla SK, Park J (2018) Classification and regression tree approach for prediction of potential hazards of urban airborne bacteria during asian dust events. Sci Rep 8(1):11823Google Scholar
  195. Yoon KY, Park CW, Byeon JH, Hwang J (2010) Design and application of an inertial impactor in combination with an ATP bioluminescence detector for in situ rapid estimation of the efficacies of air controlling devices on removal of bioaerosols. Environ Sci Technol 44(5):1742–1746Google Scholar
  196. Zamengo L, Barbiero N, Gregio M, Orrù G (2009) Combined scanning electron microscopy and image analysis to investigate airborne submicron particles: a comparison between personal samplers. Chemosphere 76(3):313–323Google Scholar
  197. Zhao, Y. et al., 2011. Investigation of the efficiencies of bioaerosol samplers for collecting aerosolized bacteria using a fluorescent tracer. I: Effects of non-sampling processes on bacterial culturability. Aerosol Science and Technology, 45(3): 423-431Google Scholar
  198. Zhen S et al (2009) A comparison of the efficiencies of a portable BioStage impactor and a reuter centrifugal sampler (RCS) high flow for measuring airborne bacteria and fungi concentrations. J Aerosol Sci 40(6):503–513Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences (CAS)LanzhouChina
  2. 2.CAS Center for Excellence in Tibetan Plateau Earth SciencesBeijingChina
  3. 3.Himalayan Environment Research Institute (HERI)KathmanduNepal

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