氣懸微粒質量分析儀應用於環境監測之效能與可行性評估

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戴于鈞(Yu-chun-Tai) 查詢紙本館藏

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環境工程研究所

論文名稱

氣懸微粒質量分析儀應用於環境監測之效能與可行性評估
(Performance and Feasibility Evaluation of APM on Application of Ambient Measurements)

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摘要(中)

大氣中的粒狀污染物(particulate matter, PM)，特別是氣動力徑小於1.0微米的微粒 (如柴油引擎所排放之廢氣)對於人類健康造成的負面影響已經由許多的流行病學及動物毒理研究證實，並被世界衛生組織的國際癌症研究中心列爲第一級的致癌物。然而這些次微米微粒在總質量貢獻的比例並不顯著。另一方面，文獻指出微粒的有效密度及構形是影響次微米微粒在呼吸道中的傳輸及沉降的重要關鍵。故微粒質量和有效密度的量測是極為重要且有助於進一步瞭解其與健康的關連性。
氣懸微粒質量分析儀(Aerosol Particle Mass Analyzer, APM)為較為新穎且廣泛應用的氣膠質量即時監測儀器，常以DMA-APM和APM-SMPS等串聯式系統來取得微粒的有效密度等特性。近年來隨著環境變遷與人類健康的議題逐漸受到重視，將APM應用於大氣環境微粒監測的相關研究日益增多。然而氣體的特性(如：氣體黏滯度和平均自由徑)卻可能隨著量測地點的不同而改變，意味著APM的操作性能可能受到環境因素的影響而有所差異。故本研究以空氣、二氧化碳與氧氣分別做為實驗的載流氣體，量測50 nm和100 nm標準微粒的質量，結果顯示黏滯度高於空氣14%的氧氣在APM的量測上有質量高估6~9%的現象，但無顯著的粒徑效應；而黏致度低於空氣25%的二氧化碳則有質量低估1~25%的情形，但有顯著的粒徑效應。且此趨勢與模擬之傳輸函數結果相符。顯示當黏滯度與標準狀態的差異過大時，將降低APM量測結果的可信度。另一方面，比較DMA-APM和APM-SMPS兩系統的量測結果後發現，以APM-SMPS系統量測實驗室產生之氣膠微粒的有效密度的偏差較DMA-APM系統大，但在環境量測的結果經後處理後是可信的。而使用DMA-APM系統所得之APM電壓分佈若有偏峰且尾部無峰肩存在時，建議需針對多粒徑效應造成的影響做校正或是改以更高的系統解析度的進行實驗，以獲得更為精確的質量量測值。

摘要(英)

Airborne particulate matter (PM), especially for submicron particles (dp,a<1.0 μm), e.g. diesel emission particle (DEP), has already been classified as group 1 carcinogenic material by IARC as a result of positive associations with various adverse human health effects. However, several scientific studies have shown that submicron particles often contribute only part of the total mass. Moreover, the fact of particle effective density and morphology play a prominent role in particle transport in respiratory tract was announced by ICRP and NCRO. Therefore, the mass distribution and effective density measurements are important, which also critical aerosol properties for understanding their health impact and associations between.
Aerosol Particle Mass Analyzer (APM) is a lately instrument for determining particle mass, as well as particle effective density which obtained by coupled system such as DMA-APM or APM-SMPS. Due to the binary interest of human health and climate change nowadays, a growing number of APM field studies were reported. However, the gas viscosity and the mean free path could vary with the environmental condition. This implies that the performance of APM might be varied with altitude. In this study, CO2 and O2 were selected as the carrier gas and compare to the case of air. Both of simulated and experimentally results show that mass of 50 and 100 nm of PSL particles shows that the peak voltage on transfer function shift with a trend of the relative Cc-μ value. Mass measured by CO2 was underestimated 1~25% and size effect was observed. While mass was overestimated 6~9% by O2 but without size effect. Comparison and detail optimize condition between DMA-APM and APM-SMPS systems were also investigate in this study. Based on experimental results, DMA-APM system is favorable to determine the effective density in lab scale studies. And a simple way to judge the necessary of multiple charge correction of APM measured data was proposed.

關鍵字(中)

★ 氣懸微粒質量分析儀
★ 傳輸函數
★ 次微米微粒
★ 有效密度

關鍵字(英)

★ Aerosol Particle Mass Analyzer (APM)
★ Transfer funciton
★ submicron particle
★ effective density

論文目次

摘要 I
Abstract II
Acknowledgments IV
Contents V
List of Figures VII
List of Tables IX
Nomenclature 1
Chapter 1. Introduction 3
Chapter 2. Theory 7
2.1 Classifying principle of APM 7
2.2 Transfer Function and Deconvolution Scheme 10
Chapter 3. Methodology 15
3.1 Experimental setup 15
3.2 Data analysis 19
Chapter 4. Results and discussion 23
4.1 Effect of Gas Viscosity on Performance of APM 23
4.2 Performance Comparison between DMA-APM and APM-SMPS Systems and to Optimize the Coupled Methods. 35
Chapter 5. Conclusion 45
References 47
Appendix I. Supplemental material for experimental data 54
Appendix II. APM variation tests 58
Appendix III. APM Operation Guideline for APM 3601 59
Review Committee Comments 62

參考文獻

Davidson, C.I., R.F. Phalen, and P.A. Solomon, Airborne Particulate Matter and Human Health: A Review. Aerosol Science and Technology, 2005. 39(8): p. 737-749.
2. Pope III, C.A. and D.W. Dockery, Health effects of fine particulate air pollution: lines that connect. Journal of the air & waste management association, 2006. 56(6): p. 709-742.
3. International Agency for Research on Cancer, I., IARC: Diesel engine exhaust carcinogenic. Press release, 2012(213).
4. International Agency for Research on Cancer, I., IARC: Outdoor air pollution a leading environmental cause of cancer deaths. 2013: International Agency for Research on Cancer.
5. Guerreiro, C., F. de Leeuw, and V. Foltescu, Air Quality in Europe: 2013 Report. 2013: Publications Office.
6. Lighty, J.S., J.M. Veranth, and A.F. Sarofim, Combustion Aerosols: Factors Governing Their Size and Composition and Implications to Human Health. Journal of the Air & Waste Management Association, 2000. 50(9): p. 1565-1618.
7. Kumar, P., et al., A review of the characteristics of nanoparticles in the urban atmosphere and the prospects for developing regulatory controls. Atmospheric Environment, 2010. 44(39): p. 5035-5052.
8. Vu, T.V., J.M. Delgado-Saborit, and R.M. Harrison, Review: Particle number size distributions from seven major sources and implications for source apportionment studies. Atmospheric Environment, 2015. 122: p. 114-132.
9. Fang, T., et al., PM2.5 water-soluble elements in the southeastern United States: automated analytical method development, spatiotemporal distributions, source apportionment, and implications for heath studies. Atmos. Chem. Phys., 2015. 15(20): p. 11667-11682.
10. Haddrell, A.E., J.F. Davies, and J.P. Reid, Dynamics of Particle Size on Inhalation of Environmental Aerosol and Impact on Deposition Fraction. Environmental Science & Technology, 2015.
11. Broday, D.M. and R. Rosenzweig, Deposition of fractal-like soot aggregates in the human respiratory tract. Journal of Aerosol Science, 2011. 42(6): p. 372-386.
12. Salma, I., et al., Effect of particle mass size distribution on the deposition of aerosols in the human respiratory system. Journal of Aerosol Science, 2002. 33(1): p. 119-132.
13. Shi, Y., et al., Nanoscale characterization of PM2. 5 airborne pollutants reveals high adhesiveness and aggregation capability of soot particles. Scientific reports, 2015. 5.
14. DeCarlo, P.F., et al., Particle Morphology and Density Characterization by Combined Mobility and Aerodynamic Diameter Measurements. Part 1: Theory. Aerosol Science and Technology, 2004. 38(12): p. 1185-1205.
15. Bau, S., et al., Determining the effective density of airborne nanoparticles using multiple charging correction in a tandem DMA/ELPI setup. Journal of Nanoparticle Research, 2014. 16(10): p. 1-13.
16. Hänel, G. and J. Thudium, Mean bulk densities of samples of dry atmospheric aerosol particles: A summary of measured data. pure and applied geophysics, 1977. 115(4): p. 799-803.
17. Kelly, W.P. and P.H. McMurry, Measurement of Particle Density by Inertial Classification of Differential Mobility Analyzer–Generated Monodisperse Aerosols. Aerosol Science and Technology, 1992. 17(3): p. 199-212.
18. Schleicher, B., S. Künzel, and H. Burtscher, Insitu measurement of size and density of submicron aerosol particles. Journal of Applied Physics, 1995. 78(7): p. 4416-4422.
19. Skillas, G., et al., High fractal-like dimension of diesel soot agglomerates. Journal of Aerosol Science, 1998. 29(4): p. 411-419.
20. Maricq, M.M., D.H. Podsiadlik, and R.E. Chase, Size Distributions of Motor Vehicle Exhaust PM: A Comparison Between ELPI and SMPS Measurements. Aerosol Science and Technology, 2000. 33(3): p. 239-260.
21. Virtanen, A., J. Ristimäki, and J. Keskinen, Method for Measuring Effective Density and Fractal Dimension of Aerosol Agglomerates. Aerosol Science and Technology, 2004. 38(5): p. 437-446.
22. Van Gulijk, C., et al., Measuring diesel soot with a scanning mobility particle sizer and an electrical low-pressure impactor: performance assessment with a model for fractal-like agglomerates. Journal of Aerosol Science, 2004. 35(5): p. 633-655.
23. Ristimäki, J., et al., On-line measurement of size distribution and effective density of submicron aerosol particles. Journal of Aerosol Science, 2002. 33(11): p. 1541-1557.
24. Symonds, J.P.R., et al., Diesel soot mass calculation in real-time with a differential mobility spectrometer. Journal of Aerosol Science, 2007. 38(1): p. 52-68.
25. Ehara, K., C. Hagwood, and K.J. Coakley, Novel method to classify aerosol particles according to their mass-to-charge ratio—Aerosol particle mass analyser. Journal of Aerosol Science, 1996. 27(2): p. 217-234.
26. Lall, A.A., et al., Nanoparticle aggregate volume determination by electrical mobility analysis: Test of idealized aggregate theory using aerosol particle mass analyzer measurements. Journal of Aerosol Science, 2008. 39(5): p. 403-417.
27. Scheckman, J.H., P.H. McMurry, and S.E. Pratsinis, Rapid Characterization of Agglomerate Aerosols by In Situ Mass−Mobility Measurements. Langmuir, 2009. 25(14): p. 8248-8254.
28. McMurry, P.H., et al., The Relationship between Mass and Mobility for Atmospheric Particles: A New Technique for Measuring Particle Density. Aerosol Science and Technology, 2002. 36(2): p. 227-238.
29. Park, K., et al., Relationship between Particle Mass and Mobility for Diesel Exhaust Particles. Environmental Science & Technology, 2003. 37(3): p. 577-583.
30. Park, K., D.B. Kittelson, and P.H. McMurry, Structural Properties of Diesel Exhaust Particles Measured by Transmission Electron Microscopy (TEM): Relationships to Particle Mass and Mobility. Aerosol Science and Technology, 2004. 38(9): p. 881-889.
31. Park, K., et al., Measurement of Inherent Material Density of Nanoparticle Agglomerates. Journal of Nanoparticle Research, 2004. 6(2): p. 267-272.
32. Tajima, N., et al., Design Considerations and Performance Evaluation of a Compact Aerosol Particle Mass Analyzer. Aerosol Science and Technology, 2013. 47(10): p. 1152-1162.
33. Olfert, J. and N. Collings, New method for particle mass classification—the Couette centrifugal particle mass analyzer. Journal of Aerosol Science, 2005. 36(11): p. 1338-1352.
34. Reavell, K., & Rushton, M. , U.K. Patent Application Number 0417657.4. 2004.
35. Malloy, Q.G.J., et al., Real-Time Aerosol Density Determination Utilizing a Modified Scanning Mobility Particle Sizer—Aerosol Particle Mass Analyzer System. Aerosol Science and Technology, 2009. 43(7): p. 673-678.
36. Leskinen, J., et al., Effective Density and Morphology of Particles Emitted from Small-Scale Combustion of Various Wood Fuels. Environmental Science & Technology, 2014. 48(22): p. 13298-13306.
37. Rissler, J., et al., Effective Density and Mixing State of Aerosol Particles in a Near-Traffic Urban Environment. Environmental Science & Technology, 2014. 48(11): p. 6300-6308.
38. Willeke, K. and P.A. Baron, Aerosol measurement. Principles, techniques and applications. Van, 1993.
39. Rissler, J., et al., Effective Density Characterization of Soot Agglomerates from Various Sources and Comparison to Aggregation Theory. Aerosol Science and Technology, 2013. 47(7): p. 792-805.
40. Tajima, N., et al., Mass Range and Optimized Operation of the Aerosol Particle Mass Analyzer. Aerosol Science and Technology, 2011. 45(2): p. 196-214.
41. Knutson, E.O. and K.T. Whitby, Aerosol classification by electric mobility: apparatus, theory, and applications. Journal of Aerosol Science, 1975. 6(6): p. 443-451.
42. Stolzenburg, M.R., An ultrafine aerosol size distribution measuring system. 1988: na.
43. Stratmann, F., et al., Differential Electrical Mobility Analysis: A Theoretical Study. Aerosol Science and Technology, 1997. 26(4): p. 368-383.
44. Hagwood, C., The DMA Transfer Function with Brownian Motion a Trajectory/Monte-Carlo Approach. Aerosol Science and Technology, 1999. 30(1): p. 40-61.
45. Li, W., L. Li, and D.-R. Chen, Technical Note: A New Deconvolution Scheme for the Retrieval of True DMA Transfer Function from Tandem DMA Data. Aerosol Science and Technology, 2006. 40(12): p. 1052-1057.
46. Ehara, K., C.R. Hagwood, and K.J. Coakley, Classification of aerosol particles according to mass-to-charge ratio. Journal of Aerosol Science, 1995. 26, Supplement 1: p. S135-S136.
47. Hagwood, C., et al., Stochastic Modeling of a New Spectrometer. Aerosol Science and Technology, 1995. 23(4): p. 611-627.
48. Emery, M., Theoretical analysis of data from DMA-APM system. Mechanical Engineering, 2005: p. 63.
49. Lall, A.A., et al., Online Nanoparticle Mass Measurement by Combined Aerosol Particle Mass Analyzer and Differential Mobility Analyzer: Comparison of Theory and Measurements. Aerosol Science and Technology, 2009. 43(11): p. 1075-1083.
50. Barone, T.L., et al., Size-Resolved Density Measurements of Particle Emissions from an Advanced Combustion Diesel Engine: Effect of Aggregate Morphology. Energy & Fuels, 2011. 25(5): p. 1978-1988.
51. Kuwata, M., Particle Classification by the Tandem Differential Mobility Analyzer–Particle Mass Analyzer System. Aerosol Science and Technology, 2015. 49(7): p. 508-520.
52. Rawat, V.K., et al., Two Dimensional Size-Mass Distribution Function Inversion from Differential Mobility Analyzer- Aerosol Particle Mass Analyzer (DMA-APM) Measurements. Journal of Aerosol Science.
53. Schmid, O., et al., Sizing of Aerosol in Gases Other Than Air Using a Differential Mobility Analyzer. Aerosol Science and Technology, 2002. 36(3): p. 351-360.
54. Karg, E., S.K. Dua, and G.A. Ferron, Performance of a differential mobility analyzer at different gas compositions. Journal of Aerosol Science, 1992. 23, Supplement 1(0): p. 389-392.
55. Marlow, W.H., P.C. Reist, and G.A. Dwiggins, Aspects of the performance of the electrical aerosol analyzer under nonideal conditions. Journal of Aerosol Science, 1976. 7(6): p. 457-462.
56. Ogren, J.A., On the operation of the electrical aerosol analyzer at reduced pressures. Journal of Aerosol Science, 1980. 11(5–6): p. 427-434.
57. Kuwata, M. and Y. Kondo, Measurements of particle masses of inorganic salt particles for calibration of cloud condensation nuclei counters. Atmos. Chem. Phys., 2009. 9(16): p. 5921-5932.
58. Zelenyuk, A., Y. Cai, and D. Imre, From Agglomerates of Spheres to Irregularly Shaped Particles: Determination of Dynamic Shape Factors from Measurements of Mobility and Vacuum Aerodynamic Diameters. Aerosol Science and Technology, 2006. 40(3): p. 197-217.
59. Lau, R. and H.K.L. Chuah, Dynamic shape factor for particles of various shapes in the intermediate settling regime. Advanced Powder Technology, 2013. 24(1): p. 306-310.
60. Wang, Z., et al., The Dynamic Shape Factor of Sodium Chloride Nanoparticles as Regulated by Drying Rate. Aerosol Science and Technology, 2010. 44(11): p. 939-953.
61. Hinds, W.C., Aerosol technology: properties, behavior, and measurement of airborne particles. 2012: John Wiley & Sons.

指導教授

蕭大智(Tai-chih Hsiao)

審核日期

2016-1-30

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