博碩士論文 106326001 詳細資訊




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姓名 陳思宇(Sih-Yu Chen)  查詢紙本館藏   畢業系所 環境工程研究所
論文名稱 能見度劣化與細及超細懸浮微粒粒徑分佈之關係 -以台中地區為例
(Relationship between Visibility and Particle Size Distribution characteristics of Fine and Ultrafine Aerosols in Taichung Area)
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摘要(中) 大氣氣膠在空氣中無所不在,其可透過影響太陽輻射而改變全球氣候,或導致區域能見度的劣化,同時也可能會造成人體健康的危害,如心血管疾病、肺功能的下降、呼吸系統的刺激等。近年來,隨著社會大眾對於空氣品質的重視,PM2.5為眾人所熟知,且對於細懸浮微粒的管制是以質量濃度為主要管制標準計量單位。然而,PM (particulate matters, 粒狀污染物)並非純物質,其為複雜的化學成分及不同粒徑之氣膠微粒混合物的統稱,因此總合之質量濃度未必能完全反映其在氣膠光學、太陽輻射或健康危害風險等影響。尤其對於大氣能見度,環境氣膠微粒的粒徑分佈更可劇烈改變其影響效應。
雖然現今已有許多國家針對氣膠的粒徑分佈進行測量,但在台灣的環境氣膠粒徑分佈則較為缺乏,再加上近期台中地區的能見度劣化議題為社會所關注。因此本研究在台中市地區建置一移動測站IMPACT (Integrated Measurements of Pollution and Aerosol Composition & Transformation),設置光學係數、質量濃度、粒徑分佈、微量氣體、重金屬元素、水溶性無機鹽離子與氣象資料等儀器同時測量。本研究主要利用掃描式電移動度分析儀(Scanning Mobility Particle Sizer, SMPS)測量粒徑範圍約10 − 1000 nm的次微米氣膠微粒粒徑分佈,及氣動粒徑分析儀(Aerodynamic Particle Sizer, APS)量測粒徑範圍約0.5 − 20 µm的細懸浮微粒粒徑分佈,進一步了解氣膠粒徑分佈與其他參數在台中地區的物化特性,並分析其在能見度劣化過程中的特徵。
研究結果顯示在總觀測期間,粒徑分布的次微米幾何平均粒徑為44.6 ± 16.9 nm,微粒平均數目濃度約為27,340 ± 17,848 (#/cm3)。微米級幾何平均粒徑約為0.79 ± 0.29 µm,微粒平均數目濃度約為103.8 ± 101.9 (#/cm3)。第二年度相較於第一年度平均粒徑偏小而數目濃度增加,總數目濃度主要受到nucleation mode的影響最劇烈。由風花圖的結果發現當南風風向且風速介於2 − 3 m/s時幾何平均粒徑較大,總數目濃度以西北風向上濃度最高。在能見度劣化時,影響能見度最主要的粒徑落在約100 nm與400 nm左右,初步推估小粒徑(100 nm)的成份主要由有機物所主導而較大粒徑(300 nm)的成份主要由硫酸鹽或硝酸鹽所主導。氣象條件的變化在能見度劣化的情況下以凌晨及早上時段相對濕度較高,約為85 − 95%。相對地,GMD在事件期的變化受到夜間NOx的異相反應及相對濕度的影響導致微粒增長。而中午發生較低風速且高溫的條件下,使得微粒數目濃度稀釋而減少。這些氣象條件或可視為提供能見度劣化的適當環境條件,並可作為預警的指標。
摘要(英) Aerosol particles are ubiquitous in atmosphere and can influence global climate and regional visibility by scattering and absorbing solar radiation. Inhalation exposure to aerosol particles could lead to adverse health effects, including respiratory irritation, changes in pulmonary function, etc. In recent years, PM2.5 is well known with the public’s emphasis on air quality. Current air quality standards of particulate matters (such as PM2.5 and PM10 standards) are based on particle mass concentrations, however, PM is a collective name for a complex chemical composition and a mixture of aerosol particles with different particle sizes. Therefore, the total mass concentration may not fully reflect the impacts on solar radiation or health risks. Especially for atmospheric visibility, particle size distribution of ambient aerosol particles can play a vital role.
Monitoring particle size distributions (PSDs) of fine and ultrafine particles in ambient environment is a challenging task but becoming regular for air quality monitoring stations worldwide. Nevertheless, the related monitoring data in Taiwan is scarce. In addition, visibility impairment in middle Taiwan (Taichung area) is receiving lots of attention over the past years. Therefore, a mobile station “IMPACT” was established in Taichung area for this study. The optical coefficient, mass concentration, particle size distribution, trace gases, heavy metal elements, water – soluble inorganic ions and meteorological data were measured simultaneously from 2017 Sep. to 2019 Aug. Scanning Mobility Particle Sizer (SMPS) and Aerodynamic Particle Sizer (APS) are employed to measure ambient aerosol PSDs ranging from 10 nm – 1000 nm and 0.5 µm – 20 µm, respectively. The results show that during the observation period, the average geometric mean diameter (GMD) of the submicron PSD is 44.6 ± 16.9 nm, and the average particle number concentration is about 27,340 ± 17,848 (#/cm3). The average GMD and the average particle number concentration of fine particle is 0.79 ± 0.29 µm and 103.8 ± 101.9 (#/cm3), respectively. Compared with the first year, the average GMD in the second year was smaller but the number concentration increased. The increasing number concentration mainly resides in the nucleation mode. Based on the wind-roses analysis, the larger aerosol particle size was generally observed when southern wind at about 2 − 3 m/s, while the highest total number concentration was accompanied with northwest winds. When visibility is degrading, the number of aerosol particles with size between 100 to 400 nm are always demonstrating a boosting growth and the growth ratio distribution behave twin-mode with peaks around 100 nm and 300 nm. It is suspected that the smaller peak growth (at around 100 nm) is caused by secondary organics generation and the larger peak growth (at around 300 nm) is due to secondary sulfate or nitrate coating.
關鍵字(中) ★ 能見度
★ 細懸浮微粒
★ 氣膠之粒徑分布
★ 掃描式電移動度粒徑分析儀
關鍵字(英) ★ visibility
★ fine particles
★ aerosol particle size distribution
★ Scanning Mobility Particle Sizer (SMPS)
論文目次 中文摘要 i
Abstract iii
誌謝 v
目錄 vi
圖目錄 ix
表目錄 xii
第一章 前言 1
1-1 研究動機 1
1-2 研究目的 4
第二章 文獻回顧 5
2-1 懸浮微粒粒徑分佈組成及特性 5
2-1-1 粒徑分佈典型特徵 5
2-1-2 粒徑分佈地域性特徵 8
2-1-3 交通影響 10
2-1-4 季節性特徵 12
2-2 懸浮微粒之物理特性 14
2-2-1 懸浮微粒有效密度 14
2-2-2 懸浮微粒形狀因子 15
2-3 能見度劣化下粒徑特性 17
2-4 氣象條件之影響 18
第三章 研究方法 20
3-1 監測地點與時間 20
3-1-1 研究地點 20
3-1-2 觀測時間 23
3-2 監測儀器 25
3-2-1 實驗系統設計 25
3-2-2 儀器原理介紹 29
3-2-3 儀器校正 31
3-3 結果分析方法 34
3-3-1 數據的品質保證管理 (QAQC) 34
3-3-2 事件期定義 35
3-3-3 粒徑模式分類 36
3-3-4 密度計算 36
3-3-5 形狀因子計算 37
3-3-6 米式理論計算 38
第四章 結果與討論 39
4-1 觀測期間粒徑分佈變化 39
4-2 各參數季節變化 43
4-3 風向來源分析 47
4-3-1 粒徑參數 47
4-3-2 PMF源解析 51
4-4 能見度劣化現象 53
4-4-1 比較兩年冬季 53
4-4-2 米式理論模型 68
第五章 結論 71
參考文獻(Reference) 73
口試委員意見回覆 82
參考文獻 1. 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.
2. Seinfeld, J.H. and S.N. Pandis, Atmospheric chemistry and physics: from air pollution to climate change. 2012: John Wiley & Sons.
3. Harrison, R.M., et al., Processes affecting concentrations of fine particulate matter (PM2. 5) in the UK atmosphere. Atmospheric Environment, 2012. 46: p. 115-124.
4. Kim, K.-H., E. Kabir, and S. Kabir, A review on the human health impact of airborne particulate matter. Environment international, 2015. 74: p. 136-143.
5. Dusek, U., et al., Size matters more than chemistry for cloud-nucleating ability of aerosol particles. Science, 2006. 312(5778): p. 1375-1378.
6. 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.
7. Donaldson, K. and W. MacNee, Potential mechanisms of adverse pulmonary and cardiovascular effects of particulate air pollution (PM10). International Journal of Hygiene and Environmental Health, 2001. 203(5-6): p. 411-415.
8. Johnston, C.J., et al., Pulmonary effects induced by ultrafine PTFE particles. Toxicology and applied pharmacology, 2000. 168(3): p. 208-215.
9. Karlsson, H.L., et al., Size-dependent toxicity of metal oxide particles—a comparison between nano-and micrometer size. Toxicology letters, 2009. 188(2): p. 112-118.
10. Peters, A., et al., Respiratory effects are associated with the number of ultrafine particles. American journal of respiratory and critical care medicine, 1997. 155(4): p. 1376-1383.
11. Penttinen, P., et al., Number concentration and size of particles in urban air: effects on spirometric lung function in adult asthmatic subjects. Environmental health perspectives, 2001. 109(4): p. 319.
12. Samet, J.M., et al., Fine particulate air pollution and mortality in 20 US cities, 1987–1994. New England journal of medicine, 2000. 343(24): p. 1742-1749.
13. Lippmann, M., et al., Association of particulate matter components with daily mortality and morbidity in urban populations. Research Report (Health Effects Institute), 2000(95): p. 5-72, discussion 73-82.
14. Ayala, A., et al., Air pollutants and sources associated with health effects. Air Quality, Atmosphere & Health, 2012. 5(2): p. 151-167.
15. Fann, N. and D. Risley, The public health context for PM 2.5 and ozone air quality trends. Air Quality, Atmosphere & Health, 2013. 6(1): p. 1-11.
16. Kulmala, M., et al., Formation and growth rates of ultrafine atmospheric particles: a review of observations. Journal of Aerosol Science, 2004. 35(2): p. 143-176.
17. Liu, S., et al., Aerosol number size distribution and new particle formation at a rural/coastal site in Pearl River Delta (PRD) of China. Atmospheric Environment, 2008. 42(25): p. 6275-6283.
18. Costabile, F., et al., Spatio-temporal variability and principal components of the particle number size distribution in an urban atmosphere. Atmospheric Chemistry and Physics, 2009. 9(9): p. 3163-3195.
19. Watson, J.G., Visibility: Science and regulation. Journal of the Air & Waste Management Association, 2002. 52(6): p. 628-713.
20. Mészáros, R., István Lagzi Róbert Mészáros Györgyi Gelybó Ádám Leelőssy.
21. Pérez, N., et al., Variability of Particle Number, Black Carbon, and PM10, PM2.5, and PM1 Levels and Speciation: Influence of Road Traffic Emissions on Urban Air Quality. Aerosol Science and Technology, 2010. 44(7): p. 487-499.
22. Tuch, T.M., et al., Long-term measurements of size-segregated ambient aerosol in two German cities located 100 km apart. Atmospheric Environment, 2003. 37(33): p. 4687-4700.
23. Seinfeld, J.H. and S.N. Pandis, Atmospheric chemistry and physics: from air pollution to climate change. 2016: John Wiley & Sons.
24. Becagli, S., et al., Evidence for heavy fuel oil combustion aerosols from chemical analyses at the island of Lampedusa: a possible large role of ships emissions in the Mediterranean. Atmos. Chem. Phys., 2012. 12(7): p. 3479-3492.
25. Prabhakar, G., et al., Spatiotemporal distribution of airborne particulate metals and metalloids in a populated arid region. Atmospheric environment, 2014. 92: p. 339-347.
26. Wehner, B. and A. Wiedensohler, Long term measurements of submicrometer urban aerosols: statistical analysis for correlations with meteorological conditions and trace gases. Atmos. Chem. Phys., 2003. 3(3): p. 867-879.
27. Hussein, T., et al., Urban aerosol number size distributions. Atmospheric Chemistry and Physics, 2004. 4(2): p. 391-411.
28. Wu, Z., et al., Particle number size distribution in the urban atmosphere of Beijing, China. Atmospheric Environment, 2008. 42(34): p. 7967-7980.
29. Yue, D., et al., Characteristics of aerosol size distributions and new particle formation in the summer in Beijing. Journal of Geophysical Research: Atmospheres, 2009. 114(D2).
30. Gao, J., et al., Measurement of aerosol number size distributions in the Yangtze River delta in China: Formation and growth of particles under polluted conditions. Atmospheric Environment, 2009. 43(4): p. 829-836.
31. Shen, X., et al., First long-term study of particle number size distributions and new particle formation events of regional aerosol in the North China Plain. Atmospheric Chemistry and Physics, 2011. 11(4): p. 1565-1580.
32. Zhang, X., et al., Characterization of particle number size distribution and new particle formation in an urban environment in Lanzhou, China. Journal of Aerosol Science, 2017. 103: p. 53-66.
33. Shen, X., et al., Characterization of submicron aerosols and effect on visibility during a severe haze-fog episode in Yangtze River Delta, China. Atmospheric Environment, 2015. 120: p. 307-316.
34. Wang, D., et al., Observation of nucleation mode particle burst and new particle formation events at an urban site in Hong Kong. Atmospheric environment, 2014. 99: p. 196-205.
35. Kanawade, V., et al., Sub-micron particle number size distributions characteristics at an urban location, Kanpur, in the Indo-Gangetic Plain. Atmospheric research, 2014. 147: p. 121-132.
36. Bullard, R.L., et al., 10-Month characterization of the aerosol number size distribution and related air quality and meteorology at the Bondville, IL Midwestern background site. Atmospheric Environment, 2017. 154: p. 348-361.
37. Németh, Z., et al., Comparison of atmospheric new particle formation events in three Central European cities. Atmospheric Environment, 2018. 178: p. 191-197.
38. Hama, S.M., et al., Sub-micron particle number size distribution characteristics at two urban locations in Leicester. Atmospheric Research, 2017. 194: p. 1-16.
39. Chen, X., et al., Modern pollen assemblages in topsoil and surface sediments of the Xingyun Lake catchment, central Yunnan Plateau, China, and their implications for interpretation of the fossil pollen record. Review of palaeobotany and palynology, 2017. 241: p. 1-12.
40. Zhu, X., et al., Regional pollution and its formation mechanism over North China Plain: A case study with ceilometer observations and model simulations. Journal of Geophysical Research: Atmospheres, 2016. 121(24): p. 14,574-14,588.
41. Wu, Z., et al., Evolution of particle number size distribution in an urban atmosphere during episodes of heavy pollution and new particle formation. Science China Earth Sciences, 2011. 54(11): p. 1772.
42. Gu, J., et al., Source apportionment of ambient particles: comparison of positive matrix factorization analysis applied to particle size distribution and chemical composition data. Atmospheric Environment, 2011. 45(10): p. 1849-1857.
43. Kittelson, D., et al., Diesel aerosol sampling in the atmosphere. SAE transactions, 2000: p. 2247-2254.
44. Vu, T.V., J.M. Delgado-Saborit, and R.M. Harrison, Particle number size distributions from seven major sources and implications for source apportionment studies. Atmospheric Environment, 2015. 122: p. 114-132.
45. Morawska, L., et al., Ambient nano and ultrafine particles from motor vehicle emissions: Characteristics, ambient processing and implications on human exposure. Atmospheric Environment, 2008. 42(35): p. 8113-8138.
46. Ristovski, Z., et al., Influence of diesel fuel sulfur on nanoparticle emissions from city buses. Environmental science & technology, 2006. 40(4): p. 1314-1320.
47. Pey, J., et al., Variations of urban aerosols in the western Mediterranean. Atmospheric Environment, 2008. 42(40): p. 9052-9062.
48. Wu, Z., et al., New particle formation in Beijing, China: Statistical analysis of a 1‐year data set. Journal of Geophysical Research: Atmospheres, 2007. 112(D9).
49. Du, P., et al., Number size distribution of atmospheric particles in a suburban Beijing in the summer and winter of 2015. Atmospheric Environment, 2018. 186: p. 32-44.
50. Venzac, H., et al., Seasonal variation of aerosol size distributions in the free troposphere and residual layer at the puy de Dôme station, France. Atmospheric Chemistry and Physics, 2009. 9(4): p. 1465-1478.
51. 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.
52. Ghosal, S. and S.A. Self, Particle size-density relation and cenosphere content of coal fly ash. Fuel, 1995. 74(4): p. 522-529.
53. Lapuerta, M., O. Armas, and A. Gómez, Diesel particle size distribution estimation from digital image analysis. Aerosol Science and Technology, 2003. 37(4): p. 369-381.
54. Park, K., et al., Relationship between particle mass and mobility for diesel exhaust particles. Environmental Science & Technology, 2003. 37(3): p. 577-583.
55. Morawska, L., et al., Relation between particle mass and number for submicrometer airborne particles. Atmospheric Environment, 1999. 33(13): p. 1983-1990.
56. Kuhlbusch, T., A. John, and H. Fissan, Diurnal variations of aerosol characteristics at a rural measuring site close to the Ruhr-Area, Germany. Atmospheric Environment, 2001. 35: p. S13-S21.
57. Khlystov, A., C. Stanier, and S. Pandis, An algorithm for combining electrical mobility and aerodynamic size distributions data when measuring ambient aerosol special issue of aerosol science and technology on findings from the fine particulate matter supersites program. Aerosol Science and Technology, 2004. 38(S1): p. 229-238.
58. Hand, J.L. and S.M. Kreidenweis, A new method for retrieving particle refractive index and effective density from aerosol size distribution data. Aerosol Science & Technology, 2002. 36(10): p. 1012-1026.
59. Pitz, M., et al., Seasonal and diurnal variation of PM2. 5 apparent particle density in urban air in Augsburg, Germany. Environmental science & technology, 2008. 42(14): p. 5087-5093.
60. Hu, M., et al., Estimation of size-resolved ambient particle density based on the measurement of aerosol number, mass, and chemical size distributions in the winter in Beijing. Environmental science & technology, 2012. 46(18): p. 9941-9947.
61. Dick, W.D., et al., Optical shape fraction measurements of submicrometre laboratory and atmospheric aerosols. Measurement Science and Technology, 1998. 9(2): p. 183.
62. Hinds, W.C., Aerosol technology: properties, behavior, and measurement of airborne particles. 1999: John Wiley & Sons.
63. 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.
64. Yang, T., et al., Gravity-current driven transport of haze from North China Plain to Northeast China in winter 2010-Part I: Observations. Sola, 2012. 8: p. 13-16.
65. Tao, M., et al., Satellite observation of regional haze pollution over the North China Plain. Journal of Geophysical Research: Atmospheres, 2012. 117(D12).
66. Wang, X., et al., Aerosol scattering coefficients and major chemical compositions of fine particles observed at a rural site in the central Pearl River Delta, South China. Journal of Environmental Sciences, 2012. 24(1): p. 72-77.
67. Jihua, T., et al., Chemical characteristics of PM2. 5 during a typical haze episode in Guangzhou. Journal of Environmental Sciences, 2009. 21(6): p. 774-781.
68. Wang, X., et al., Particle number concentration, size distribution and chemical composition during haze and photochemical smog episodes in Shanghai. Journal of Environmental Sciences, 2014. 26(9): p. 1894-1902.
69. Castro, A., et al., Aerosol size distribution in precipitation events in León, Spain. Atmospheric Research, 2010. 96(2-3): p. 421-435.
70. Birmili, W., et al., Atmospheric particle number size distribution in central Europe: Statistical relations to air masses and meteorology. Journal of Geophysical Research: Atmospheres, 2001. 106(D23): p. 32005-32018.
71. Charron, A. and R.M. Harrison, Primary particle formation from vehicle emissions during exhaust dilution in the roadside atmosphere. Atmospheric Environment, 2003. 37(29): p. 4109-4119.
72. Wang, Y., et al., Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Science China Earth Sciences, 2014. 57(1): p. 14-25.
73. Shi, J.P. and R.M. Harrison, Investigation of ultrafine particle formation during diesel exhaust dilution. Environmental Science & Technology, 1999. 33(21): p. 3730-3736.
74. Baxla, S., et al., Analysis of diurnal and seasonal variation of submicron outdoor aerosol mass and size distribution in a northern Indian city and its correlation to black carbon. Aerosol Air Qual. Res, 2009. 9(4): p. 458-469.
75. Kaul, D., et al., Secondary organic aerosol: a comparison between foggy and nonfoggy days. Environmental science & technology, 2011. 45(17): p. 7307-7313.
76. Quan, J., et al., Analysis of the formation of fog and haze in North China Plain (NCP). Atmospheric Chemistry and Physics, 2011. 11(15): p. 8205-8214.
77. Wu, C. and J.Z. Yu, Determination of primary combustion source organic carbon-to-elemental carbon (OC/EC) ratio using ambient OC and EC measurements: secondary OC-EC correlation minimization method. Atmos. Chem. Phys., 2016. 16(8): p. 5453-5465.
78. Tsekeri, A., et al., Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing. Atmospheric Measurement Techniques, 2017. 10(1): p. 83-107.
79. Hung, H.-M., et al., Enhancement of the hygroscopicity parameter kappa of rural aerosols in northern Taiwan by anthropogenic emissions. Atmospheric Environment, 2014. 84: p. 78-87.
80. Zhang, Z., et al., Analysis of extinction properties as a function of relative humidity using a <i>κ</i>-EC-Mie model in Nanjing. Atmospheric Chemistry and Physics, 2017. 17(6): p. 4147-4157.
81. Xu, W., et al., Impact of emission controls on air quality in Beijing during APEC 2014: Implications from water-soluble ions and carbonaceous aerosol in PM2. 5 and their precursors. 2019. 210: p. 241-252.
82. Beevers, S.D., et al., Trends in NOx and NO2 emissions from road traffic in Great Britain. Atmospheric Environment, 2012. 54: p. 107-116.
83. Zhang, Z., et al., Analysis of extinction properties as a function of relative humidity using a κ-EC-Mie model in Nanjing. Atmospheric Chemistry and Physics, 2017. 17(6): p. 4147-4157.
指導教授 蕭大智 江康鈺(Ta-Chih Hsiao Kung-Yuh Chiang) 審核日期 2020-3-17
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