雲林斗六PM2.5濃度變化與氣膠光學特性及氣象條件之關聯性研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：134

、訪客IP：3.15.31.27

姓名

陳柏霖(Po-Ling Chen) 查詢紙本館藏

畢業系所

大氣科學學系

論文名稱

雲林斗六PM2.5濃度變化與氣膠光學特性及氣象條件之關聯性研究

相關論文

★ 鹿林山背景站大氣輻射及氣膠輻射驅動力之研究	★ 中南半島生質燃燒氣膠濃度分布之年際變化與其對區域環境衝擊研究
★ 中壢地區光達消光散射比之長期分析與污染物關聯性研究	★ 臺灣大氣背景PM2.5質量濃度之推估
★ Mapping Surface Solar Radiation with Satellite Data over Taiwan	★ 開發適用於大氣邊界層觀測的無人機系統
★ 利用AERONET資料解析中南半島地區氣膠種類及成分	★ 氣膠對臺灣北部暖雲微物理和毛雨的影響
★ Characteristics and Corrections of Thermal Offset for Secondary Standard Pyranometers	★ 氣膠對臺灣中部平原夏季降水日變化之影響
★ 中南半島生質燃燒氣膠傳送動力機制及區域氣候反饋	★ 2019年春季泰國北部無人機觀測實驗: 邊界層特徵與氣膠垂直分布之研究
★ Investigating hygroscopic cloud-seeding effects in liquid-water clouds in northern Taiwan: in-situ measurements and model simulation	★ 整合無人機與光達觀測解析斗六地區空污事件之演變過程
★ 氣膠光學及微物理反演法開發：以鹿林山大氣背景站應用為例	★ 利用向日葵8號衛星及單層輻射模式反演地面輻射量

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

雲林縣近三年(2013-2015年)為全台灣污染最嚴重之縣市，轄區內之斗六地區污染源眾多，污染成因及氣膠種類複雜，因此本研究於較少受境外傳送污染影響之秋季，分析斗六及鄰近區域2005-2015年長期區域PM2.5濃度時空分布特性及與氣象因子相關性，於2015年秋季觀測期間進一步以氣膠光學儀器分析斗六地表和垂直氣柱氣膠光學特性，配合氣膠垂直分布及氣象條件資訊，希望解釋影響斗六地區地表氣膠濃度及特性之因素。

分析2005-2015年秋季斗六、崙背、台西空品站PM2.5濃度日平均值顯示斗六PM2.5濃度最高，台西最低，但污染事件日PM2.5濃度增加比例以台西最多，斗六最少，三站PM2.5濃度逐年下降，斗六下降趨勢最為明顯，PM2.5濃度小時值顯示斗六PM2.5濃度於日間上升夜間下降，台西站於夜間上升日間下降，為海陸風環流造成之差異。斗六站PM2.5濃度日平均與相對濕度、風速、溫度、垂直大氣穩定度相關係數(r)值分別為-0.30、-0.29、-0.18、0.19，四變數線性回歸R2值為0.22，代表上述氣象條件變異對PM2.5濃度變化造成22 %之影響。

由2015年觀測期間結果分析氣象條件對氣膠特性之影響，顯示相對濕度、風速、溫度與吸光性氣膠相關性較散光性氣膠佳，於污染事件日溫度與吸光係數r值達0.63，氣象條件於污染事件日時對氣膠粒徑有較大影響，r值分別為-0.60、0.50、0.56。分析垂直氣柱氣膠光學厚度(AOD)與地面PM2.5濃度相關性為正相關，但兩者於污染事件日為負相關，推測平時斗六地區主要污染源為當地排放和短程近地表傳送，污染事件日時可能有較多高空污染物影響地表，此現象可以由光達垂直氣膠分布發展特徵解析出來，而觀測期間PM2.5濃度與邊界層頂高度成正相關，亦說明垂直混和作用較強、地表與高空大氣交換較多時，PM2.5濃度較高。個案分析結果顯示，造成斗六地表污染PM2.5濃度提升之原因為：地表污染排放、海陸風環流輸入沿海地區污染物、夜間高空殘餘層於日間因對流作用下降至地表、垂直大氣穩定度高使污染物不易擴散，以上結果可作為日後地表污染預報及防治之參考。

摘要(英)

In the last three years (2013-2015), the most serious air pollution county in Taiwan is Yunlin. Douliu city, the capital of Yunlin, has many emission sources of particulate matter indicating complicated aerosol environment. In this study, we use 10 years (2005-2015) PM2.5 data of Douliu aera in autumn to analysis its temporal variation, spatial distribution and correlation with meteorology conditions. Aerosol data obtaining from an experiment in 2015 autumn at Douliu city has been used to further analyze aerosol vertical distribution and aerosol optical properties in both surface and vertical column. We try to use meteorology data, aerosol vertical distribution and the aerosol optics both at surface and vertical column to understand what the reason of aerosol concentration and the deterioration of air quality in Douliu city in autumn.

　　The daily mean PM2.5 concentrations for Taixi, Lunbei, and Douliu from 11 years (2005-2015) fall season show the highest value for Douliu and the lowest value for Taixi. However, during polluted events, Taixi PM2.5 concentration growth rates is highest and Douliu is lowest. All three sites show decreasing trend of PM2.5 concentrations in the past ten years, especially for Douliu site. Hourly PM2.5 data reveal Douliu concentration increase at daytime and decrease at nighttime, whereas an opposite day-night trend for Taixi, suggesting it may in relation to the local land-sea breeze circulation. Correlation coefficients (R) between four meteorology conditions (relative humidity, wind speed, temperature, and vertical stability) and PM2.5 concentrations at Douliu are -0.30, -0.29, -0.18, 0.19, respectively. If we consider all of above meteorological parameters together with PM2.5 concentration, R-squared can reach 0.22. It suggests that 22 percent of PM2.5 concentration variation is associated with meteorology conditions.

Results from 2015 field experiment showed that three meteorology parameters (relative humidity, wind speed and temperature) have better correlation coefficient with higher absorption aerosols (i.e. low single-scattering albedo). Correlation coefficient between temperature and absorption coefficient is 0.63 durning polluted event period. Higher correlation coefficient between meteological prameters and aerosol size are found to be -0.60, 0.50, 0.56 for RH, wind speed, and temperature, respectively. PM2.5 concentration shows positive correlation with AOD in the experimental period in general but shows a negative correlation durning polluted event period. This result implies the main sources of air pollution are local emissions and short-term near ground transport during the normal days. As contrast, lidar observation reveals high altitude aerosols downward transport to the ground durning polluted days. Positive correlation between PM2.5 concentration and PBL height also suggests that PM2.5 concentration will increase when atmospheric mixing is stronger. Results from case studies show that the increasing of surface air pollution in Douliu are due to local emission, aerosol transport by land-sea breeze circulation, nighttime residual layer downward to the surface by atmospheric vertical convection, and poor diffusion by high vertical stability. This study has implications on air quality diagnostic, forecast, as well as control policy making for the high PM2.5 area such as Douliu.

關鍵字(中)

★ 氣膠光學特性
★ 光達
★ 太陽光度計
★ 垂直大氣穩定度

關鍵字(英)

論文目次

摘要 i
Abstract iii
致謝 v
目錄 vi
表目錄 viii
圖目錄 ix
1.　前言 1
1.1 研究動機 1
1.2 研究目的 2
2.　文獻回顧 4
2.1光達的發展與應用 4
2.2氣膠光學特性研究 5
2.3定義垂直大氣穩定度與光達反演邊界層頂方法 9
2.4台灣中部地區PM2.5濃度及氣象因子相關性研究 10
3.　研究方法 12
3.1 研究流程架構 12
3.2 實驗時間與地點 12
3.3 實驗設備與觀測原理 12
3.3.1 太陽光度計(Sun-photometer) 12
3.3.2 微脈衝光達(Micro-Pulse Lidar, MPL) 14
3.3.3 積分式散光儀(Integrating Nephelometer) 15
3.3.4 黑碳儀(Aethalometer) 16
3.4 氣膠光學參數 16
3.4.1 氣膠光學厚度(Aerosol Optical Depth, AOD或τ) 16
3.4.2 Ångström exponent (AE, ) 17
3.4.3 單次散射反照率(Single-scattering albedo, SSA, ω0) 17
3.5 定義垂直大氣穩定度 18
3.6 定義邊界層頂高度 19
4.　結果與討論 20
4.1 長期污染特性分析 20
4.2 斗六垂直大氣穩定度與氣象參數對PM2.5濃度影響分析 22
4.3 斗六空品站觀測期間資料分析 25
4.3.1 地表污染物特性與氣象條件相關性分析 25
4.3.2 垂直氣柱與垂直剖面污染特性及與地表污染物相關性分析 28
4.4 個案污染特性分析 30
4.4.1 個案一(9/16-9/19) 30
4.4.2 個案二(9/22-9/23) 31
5.　結論 34
6.　未來展望 37
參考文獻 38

參考文獻

王俊凱, & 鄧亦翔. (2014). 夏季斗六地區大氣粒狀物粒徑成份初探. 雲林科技大學環境與安全衛生工程學系實務專題.
江智偉, & 倪簡白. (2007). 光達遙測中壢地區夜間邊界層變化和低層噴流之討論. 大氣科學, 35(1), 1-11.
李慶偉. (2014). 中壢地區光達消光散射比之長期分析與污染物關聯性研究. 中央大學大氣物理研究所學位論文, 1-89.
林毓珣, 白凱棣, 彭義強, & 林緯翰. (2016). 雲林縣細懸浮微粒(PM2.5)污染來源調查分析暨空品預警應變計畫. 103-050
徐開炫. (2011). 2009 年春季鹿林山背景站氣膠垂直分佈與光學特性分析. 中央大學大氣物理研究所學位論文, 1-133.
徐睿鴻. (2007). 鹿林山與中壢氣膠光學垂直特性之監測與比較. 中央大學大氣物理研究所學位論文, 1-107.
郭俊江. (2006). 光達及太陽輻射儀之應用: 2005 中壢氣膠光學垂直特性及邊界層高度之變化. 中央大學大氣物理研究所學位論文, 1-124.
黃淑倫, 林裕清, 郭素娥, 紀妙青, 林玠模, 周姜廷, & 黃友珊. (2016). 嘉南地區細懸浮微粒濃度與氣象因子相關性分析: 2006-2014. 台灣公共衛生雜誌, 35(6), 575-586.
溫志中, 方國權, & 蔡立宏. (2006). 台中港區空氣懸浮微粒特性研究. 港灣報導, (75), 39-45.
賈浩平. (2008). 微脈衝光達及太陽輻射儀之應用: 2005-2007 年中壢地區氣膠光學垂直特性分析. 中央大學大氣物理研究所學位論文.
謝政廷. (2013). 雲林地區河川揚塵及沙塵暴事件懸浮微粒之化學組成特性. 環球科技大學資源管理研究所學位論文.

錢滄海, & 陳奕愷. (2012). 濁水溪下游懸浮微粒與氣象因子關係之研究. 水土保持學報44(4) : 391 – 406.
Anderson, T. L., & Ogren, J. A. (1998). Determining aerosol radiative properties using the TSI 3563 integrating nephelometer. Aerosol Science and Technology, 29(1), 57-69.
Ansmann, A., Tesche, M., Groß, S., Freudenthaler, V., Seifert, P., Hiebsch, A., ... & Wiegner, M. (2010). The 16 April 2010 major volcanic ash plume over central Europe: EARLINET lidar and AERONET photometer observations at Leipzig and Munich, Germany. Geophysical Research Letters, 37(13).
Arnott, W. P., Hamasha, K., Moosmüller, H., Sheridan, P. J., & Ogren, J. A. (2005). Towards aerosol light-absorption measurements with a 7-wavelength aethalometer: Evaluation with a photoacoustic instrument and 3-wavelength nephelometer. Aerosol Science and Technology, 39(1), 17-29.
Barrett, E. W., & Ben-Dov, O. (1967). Application of the lidar to air pollution measurements. Journal of Applied Meteorology, 6(3), 500-515.
Campbell, J. R., Hlavka, D. L., Welton, E. J., Flynn, C. J., Turner, D. D., Spinhirne, J. D., ... & Hwang, I. H. (2002). Full-time, eye-safe cloud and aerosol lidar observation at atmospheric radiation measurement program sites: Instruments and data processing. Journal of Atmospheric and Oceanic Technology, 19(4), 431-442.
Chen, M. L., Mao, I. F., & Lin, I. K. (1999). The PM2.5 and PM10 particles in urban areas of Taiwan. Science of the total environment, 226(2), 227-235.
Chen, Z., Liu, W., Heese, B., Althausen, D., Baars, H., Cheng, T., ... & Zhang, T. (2014). Aerosol optical properties observed by combined Raman‐elastic backscatter lidar in winter 2009 in Pearl River Delta, south China. Journal of Geophysical Research: Atmospheres, 119(5), 2496-2510.
Cheng, M. T., Chou, W. C., Chio, C. P., Hsu, S. C., Su, Y. R., Kuo, P. H., ... & Chou, C. C. K. (2008). Compositions and source apportionments of atmospheric aerosol during Asian dust storm and local pollution in central Taiwan. Journal of atmospheric chemistry, 61(2), 155-173.
Chiang, C. W., Chen, W. N., Liang, W. A., Das, S. K., & Nee, J. B. (2007). Optical properties of tropospheric aerosols based on measurements of lidar, sun-photometer, and visibility at Chung-Li (25 N, 121 E). Atmospheric Environment, 41(19), 4128-4137.
Chio, C. P., Cheng, M. T., & Wang, C. F. (2004). Source apportionment to PM10 in different air quality conditions for Taichung urban and coastal areas, Taiwan. Atmospheric Environment, 38(39), 6893-6905.
Collis, R. T. (1965). Lidar observation of cloud. Science, 149(3687), 978-981.
Cropper, P. M., Hansen, J. C., & Eatough, D. J. (2013). Measurement of light scattering in an urban area with a nephelometer and PM2.5 FDMS TEOM monitor: accounting for the effect of water. Journal of the Air & Waste Management Association, 63(9), 1004-1011.
Ding, A. J., Huang, X., Nie, W., Sun, J. N., Kerminen, V. M., Petäjä, T., ... & Chi, X. G. (2016). Enhanced haze pollution by black carbon in megacities in China. Geophysical Research Letters, 43(6), 2873-2879.
Dubovik, O., & King, M. D. (2000). A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. Journal of Geophysical Research: Atmospheres, 105(D16), 20673-20696.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., ... & Slutsker, I. (2002). Variability of absorption and optical properties of key aerosol types observed in worldwide locations. Journal of the atmospheric sciences, 59(3), 590-608.
Eck, T. F., Holben, B. N., Dubovik, O., Smirnov, A., Goloub, P., Chen, H. B., ... & Ji, Q. (2005). Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid‐Pacific. Journal of Geophysical Research: Atmospheres, 110(D6).
Fiocco, G., & Smullin, L. D. (1963). Detection of scattering layers in the upper atmosphere (60–140 km) by optical radar. Nature, 199(4900), 1275-1276.
Flamant, C., Pelon, J., Flamant, P. H., & Durand, P. (1997). Lidar determination of the entrainment zone thickness at the top of the unstable marine atmospheric boundary layer. Boundary-Layer Meteorology, 83(2), 247-284.
Hansen, A. D. A., Rosen, H., & Novakov, T. (1984). The aethalometer—an instrument for the real-time measurement of optical absorption by aerosol particles. Science of the Total Environment, 36, 191-196.
Holben, B. N., Eck, T. F., Slutsker, I., Tanre, D., Buis, J. P., Setzer, A., ... & Lavenu, F. (1998). AERONET—A federated instrument network and data archive for aerosol characterization. Remote sensing of environment, 66(1), 1-16.
Hsu, C. H., & Cheng, F. Y. (2016). Classification of weather patterns to study the　　　　　influence of meteorological characteristics on PM 2.5 concentrations in Yunlin　County, Taiwan. Atmospheric Environment, 144, 397-408.
Hulburt, E. O. (1937). Observations of a searchlight beam to an altitude of 28 kilometers. JOSA, 27(11), 377-382.
Jacob, D. J., & Winner, D. A. (2009). Effect of climate change on air quality. Atmospheric environment, 43(1), 51-63.
Klett, J. D. (1981). Stable analytical inversion solution for processing lidar returns. Applied Optics, 20(2), 211-220.
Klett, J. D. (1985). Lidar inversion with variable backscatter/extinction ratios. Applied Optics, 24(11), 1638-1643.
Menut, L., Flamant, C., Pelon, J., & Flamant, P. H. (1999). Urban boundary-layer height determination from lidar measurements over the Paris area. Applied Optics, 38(6), 945-954.
Müller, D., Ansmann, A., Mattis, I., Tesche, M., Wandinger, U., Althausen, D., & Pisani, G. (2007). Aerosol‐type‐dependent lidar ratios observed with Raman lidar. Journal of Geophysical Research: Atmospheres, 112(D16).
Quan, J., Gao, Y., Zhang, Q., Tie, X., Cao, J., Han, S., ... & Zhao, D. (2013). Evolution of planetary boundary layer under different weather conditions, and its impact on aerosol concentrations. Particuology, 11(1), 34-40.
Park, S. S., Hansen, A. D., & Cho, S. Y. (2010). Measurement of real time black carbon for investigating spot loading effects of Aethalometer data. Atmospheric Environment, 44(11), 1449-1455.
Raut, J. C., & Chazette, P. (2009). Assessment of vertically-resolved PM10 from mobile lidar observations. Atmospheric Chemistry and Physics, 9(21), 8617-8638.
Soni, K., Singh, S., Bano, T., Tanwar, R. S., Nath, S., & Arya, B. C. (2010). Variations in single scattering albedo and Angstrom absorption exponent during different seasons at Delhi, India. Atmospheric environment, 44(35), 4355-4363.
Tai, A. P., Mickley, L. J., & Jacob, D. J. (2010). Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change. Atmospheric Environment, 44(32), 3976-3984.
Wang, S. H., Tsay, S. C., Lin, N. H., Chang, S. C., Li, C., Welton, E. J., ... & Kuo, C. C. (2013). Origin, transport, and vertical distribution of atmospheric pollutants over the northern South China Sea during the 7-SEAS/Dongsha Experiment. Atmospheric environment, 78, 124-133.
Wang, S. H., Welton, E. J., Holben, B. N., Tsay, S. C., Lin, N. H., Giles, D., ... & Chen, W. N. (2015). Vertical distribution and columnar optical properties of springtime biomass-burning aerosols over Northern Indochina during 2014 7-SEAS campaign. Aerosol Air Qual. Res, 15, 2037-2050.
Wang, S. Y., Hipps, L. E., Chung, O. Y., Gillies, R. R., & Martin, R. (2015). Long-term winter inversion properties in a mountain valley of the western United States and implications on air quality. journal of applied meteorology and climatology, 54(12), 2339-2352.
Whiteman, D. N., Rush, K., Veselovskii, I., Cadirola, M., Comer, J., Potter, J. R., & Tola, R. (2007). Demonstration measurements of water vapor, cirrus clouds, and carbon dioxide using a high-performance Raman lidar. Journal of atmospheric and oceanic technology, 24(8), 1377-1388.
Witschas, B., Rahm, S., Wagner, J., & Dörnbrack, A. (2016). Airborne Coherent Doppler Wind Lidar measurements of vertical and horizontal wind speeds for the investigation of gravity waves.
Xia, X. (2011). Variability of aerosol optical depth and Angstrom wavelength exponent derived from AERONET observations in recent decades. Environmental Research Letters, 6(4), 044011.
Xin, J., Zhang, Q., Wang, L., Gong, C., Wang, Y., Liu, Z., & Gao, W. (2014). The empirical relationship between the PM2.5 concentration and aerosol optical depth over the background of North China from 2009 to 2011. Atmospheric Research, 138, 179-188.
Yu, C., & Yi, F. (2008). Atmospheric temperature profiling by joint Raman, Rayleigh and Fe Boltzmann lidar measurements. Journal of Atmospheric and Solar-Terrestrial Physics, 70(10), 1281-1288.

指導教授

王聖翔(Sheng-Hsiang Wang)

審核日期

2017-8-24

推文