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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 環境衛生研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48733
完整後設資料紀錄
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dc.contributor.advisor吳章甫(Chang-Fu Wu)
dc.contributor.authorShih-Chun Linen
dc.contributor.author林士鈞zh_TW
dc.date.accessioned2021-06-15T07:10:58Z-
dc.date.available2011-03-03
dc.date.copyright2011-03-03
dc.date.issued2010
dc.date.submitted2010-10-13
dc.identifier.citation1. Wu, C.F., et al., Developing and Evaluating Techniques for Localizing Pollutant
Emission Sources with Open-Path Fourier Transform Infrared Measurements and Wind Data; Journal of the Air & Waste Management Association. 2008. 58(10): p. 1360.
2. Chen, C.L. Source location and characterization of volatile organic compound
emissions at a petrochemical plant in Kaohsiung, Taiwan; Journal of the Air and Waste Management Association. 2005. 55(10): p. 1487.
3. Chen, C.L. Mapping and profile of emission sources for airborne volatile
organic compounds from process regions at a petrochemical plant in Kaohsiung, Taiwan; Journal of the Air and Waste Management Association. 2006. 56(6): p. 824.
4. Hashmonay, R.A. Yost M.G. Localizing gaseous fugitive emission sources by
combining real-time optical remote sensing and wind data; Journal of the Air and Waste Management Association. 1999. 49(11): p. 1374.
5. Zhao, W. Source identification of volatile organic compounds in Houston, Texas;
Environmental Science and Technology. 2004. 38(5): p. 1338.
6. Chang, S.Y.; C.F. Wu Using 2-D Radial Plume Mapping Technique for
Source Localization: Evaluation of Reconstruction Algorithms; National Taiwan University, Master thesis. 2008.
7. Thomson, L.C. An improved algorithm for locating a gas source using inverse
methods; Atmospheric Environment. 2007. 41(6): p. 1128.
8. Chen, C.L. Location and Characterization of VOC Emissions at a Petrochemical
Plant in Taiwan; Environmental Forensics. 2006. 7(2): p. 159.
9. Drescher, A.C. Stationary and time-dependent indoor tracer-gas concentration
profiles measured by OP-FTIR remote sensing and SBFM-computed tomography; Atmospheric Environment. 1996. 31(5): p. 727.
10. Hashmonay, R.A. Computed tomography of air pollutants using radial
scanning path-integrated optical remote sensing; Atmospheric Environment. 1999. 33(2): p. 267.
11. U.S. EPA. Other Test Method OTM-10: Optical Remote Sensing for Emission
Characterization from Non-Point Sources. 2006.
12. Smith, B.C. Fundamentals of Fourier Transform Infrared Spectroscopy. Boca
Raton: CRC Press. 1996.
13. Todd, L. Remote sensing and computed tomography in industrial hygiene;
AIHA Journal, 1990. 51(4): p. 224.
14. Hashmonay, R.A. Field evaluation of a method for estimating gaseous fluxes
from area sources using open-path Fourier transform infrared; Environmental Science and Technology. 2001. 35(11): p. 2309.
15. Ren, Y. Combination of neural network and SBFM algorithm for monitoring
VOCs distribution by open path FTIR spectrometry; Instrumentation Science and Technology. 2007. 35(1): p. 1.
16. U.S. EPA. Compendium Method TO-16: Long-Path Open-Path Fourier
Transform Infrared Monitoring of Atmospheric Gases. 1999.
17. T.W. IOSH. Establish The Fourier Transfer Infrared Monitoring Technique.
1999.
18. T.W. E.A.L. 空氣中揮發性化合物篩檢方法-開徑式傅立葉轉換紅外光
光譜分析法. 2005.
19. Holmes, N.S. A review of dispersion modeling and its application to the
dispersion of particles: An overview of different dispersion models available;
Atmospheric Environment, 2006. 40(30): p. 5902.
20. Turner, D.B. Workbook of atmospheric dispersion estimates : an introduction to
dispersion modeling. Lewis Publishers. 1996.
21. Drescher, A.C. Novel approach for tomographic reconstruction of gas
concentration distributions in air: Use of smooth basis functions and simulated annealing; Atmospheric Environment, 1996. 30(6): p. 929.
22. U.S. EPA. On-Site Meteorological Program Guidance for Regulatory Modeling
Appications. 1987.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48733-
dc.description.abstract本研究之目的是使用光學遙測偵測儀器-開徑式傅立葉轉換紅外光光譜儀(Open Path Fourier Transform Infrared Spectroscopy, OP-FTIR)結合一維輻射光徑煙流分布重建法 (1D-RPM) 來推估地面污染源之位置(污染源高度接近於地面)。本研究使用Smooth Basis Function Minimization (SBFM)重建法來重建下風處濃度最高的位置,再結合濃度最高的位置與對應的風向資料回推污染源之位置。此研究的獨特性為藉由建立兩條互相垂直的測線取代先前研究中所使用的單一下風處測線,來減少推估污染源的不確定性及縮短推估釋放源的位置與真實位置的距離。
在真實的情況下,污染源的位置是未知的,所以在電腦模擬部分,我們模擬了在200公尺乘以200公尺的區域中所有可能的污染源位置,來比較使用兩條1D-RPM測線與先前研究的差異。我們以估計位置出現頻率來評估定位之結果,使用兩條1D-RPM測線除了在推估污染源的準確性有所提升以外,可準確定位污染源的範圍也大幅增加。此研究也發現下風處的三道光徑中,濃度最高位置的比例不同可能會影響推估的準確性。
在戶外實地實驗中,使用OP-FTIR結合兩條1D-RPM測線來定位人為釋放的污染源(追蹤氣體)。實驗的結果與電腦模擬相似,使用兩條1D-RPM測線縮短了推估釋放源位置與真實位置的距離,回推的不確定性也較低。推估釋放源位置與真實位置的距離小於40公尺。
zh_TW
dc.description.abstractThis paper reports the computational simulation and field experimental results by using the OP-FTIR spectroscopy with the 1D-RPM technology to locate the ground-level emission sources. The objective of this study is to improve the 1D-RPM technology by adding one additional monitoring line to reduce the uncertainty of source location results and the distance between the estimated source and the real source location.
The smooth basis function minimization (SBFM) algorithm was used to reconstruct the peak location of the plume. Combining the peak location of downwind concentrations along the monitoring line and the wind data gives the estimated source locations.
In the computational simulation study, we propose using the concept of “error map” to indicate the performance and uncertainty of the two-line 1D-RPM. The error map shows that using two-line 1D-RPM can locate the sources more accurately, and cover wider area than using one monitoring line only. We also found the locating result varied as the proportion of the reconstructed peak locations.
In the field experiment, the distance between the region having highest density of estimated of source location and the real source location (DIST) and the uncertainty area are smaller by using two-line 1D-RPM than original one line 1D-RPM. The DIST is smaller than 40 meter (20 percent of the size of the experimental domain) by using two-line 1D-RPM.
en
dc.description.provenanceMade available in DSpace on 2021-06-15T07:10:58Z (GMT). No. of bitstreams: 1
ntu-99-R97844014-1.pdf: 1361410 bytes, checksum: 050e256092847caa04734c8a8b239110 (MD5)
Previous issue date: 2010
en
dc.description.tableofcontentsCONTENTS
ACKNOWLEDGEMENT I
中文摘要 III
ABSTRACT IV
1. INTRODUCTION 1
1.1. SOURCE LOCATING METHODS 1
1.2. TWO-DIMENSIONAL RADIAL PLUME MAPPING TECHNIQUE 2
1.3. ONE-DIMENSIONAL RADIAL PLUME MAPPING (1D-RPM) TECHNIQUE 3
1.4. OPEN-PATH FOURIER TRANSFORMED INFRARED SPECTROMETER (OP-FTIR) 5
1.5. STUDY OBJECTIVES 6
2. MATERIALS AND METHODS 9
2.1. SIMULATION STUDY 9
2.1.1. Generating Downwind Concentration Distributions 10
2.1.2. Smooth Basis Function Minimization (SBFM) Reconstruction 12
2.1.3. Source Localization 14
2.1.4. Uncertainty Map (Density Plot) Designation 15
2.1.5. Error Map Designation 16
2.2. FIELD EXPERIMENT 17
2.2.1. Data Collection 17
2.2.2. Data Analysis 19
3. RESULTS AND DISCUSSION 29
3.1. COMPUTATIONAL SIMULATION RESULTS 29
3.2. FIELD EXPERIMENT RESULTS 37
4. CONCLUSIONS AND RECOMMENDATIONS 59
REFERENCES 62
APPENDIX 64
dc.language.isoen
dc.subject空氣污染zh_TW
dc.subject污染物定位zh_TW
dc.subject開徑式傅立葉轉換紅外光光譜儀zh_TW
dc.subject一維輻射光徑煙流分布重建法zh_TW
dc.subject光學遙測zh_TW
dc.subject逸散源zh_TW
dc.subjectoptical remote sensingen
dc.subjectair pollutanten
dc.subjectemissionen
dc.subjectsource localizationen
dc.subject1D-RPMen
dc.subjectOP-FTIRen
dc.title以雙測線之一維輻射光徑煙流分布重建法定位污染源zh_TW
dc.titleSource Localization with One-dimensional Radial Plume Mapping Technique Using Two Monitoring Linesen
dc.typeThesis
dc.date.schoolyear99-1
dc.description.degree碩士
dc.contributor.oralexamcommittee謝祝欽,劉希平,吳焜裕
dc.subject.keyword污染物定位,開徑式傅立葉轉換紅外光光譜儀,一維輻射光徑煙流分布重建法,光學遙測,逸散源,空氣污染,zh_TW
dc.subject.keywordsource localization,OP-FTIR,1D-RPM,optical remote sensing,emission,air pollutant,en
dc.relation.page91
dc.rights.note有償授權
dc.date.accepted2010-10-14
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept環境衛生研究所zh_TW
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