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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蕭大智 | zh_TW |
dc.contributor.advisor | Ta-Chih Hsiao | en |
dc.contributor.author | 賴弘恩 | zh_TW |
dc.contributor.author | Hong-En Lai | en |
dc.date.accessioned | 2025-02-25T16:21:49Z | - |
dc.date.available | 2025-02-26 | - |
dc.date.copyright | 2025-02-25 | - |
dc.date.issued | 2025 | - |
dc.date.submitted | 2025-02-08 | - |
dc.identifier.citation | Ahsanullah, M., Nevzorov, V. B., & Shakil, M. (2013). An introduction to order statistics (Vol. 8). Springer.
Apte, J. S., Marshall, J. D., Cohen, A. J., & Brauer, M. (2015). Addressing global mortality from ambient PM2.5 Environmental science & technology, 49(13), 8057-8066. https://doi.org/https://doi.org/10.1021/acs.est.5b01236 Bäumer, D., Vogel, B., Versick, S., Rinke, R., Möhler, O., & Schnaiter, M. (2008). Relationship of visibility, aerosol optical thickness and aerosol size distribution in an ageing air mass over South-West Germany. Atmospheric Environment, 42(5), 989-998. https://doi.org/https://doi.org/10.1016/j.atmosenv.2007.10.017 Bian, Q., Huang, X. H. H., & Yu, J. Z. (2014). One-year observations of size distribution characteristics of major aerosol constituents at a coastal receptor site in Hong Kong – Part 1: Inorganic ions and oxalate. Atmos. Chem. Phys., 14(17), 9013-9027. https://doi.org/10.5194/acp-14-9013-2014 Chen, D., Zhao, Y., Zhang, J., Yu, H., & Yu, X. (2020). Characterization and source apportionment of aerosol light scattering in a typical polluted city in the Yangtze River Delta, China. Atmos. Chem. Phys., 20(17), 10193-10210. https://doi.org/10.5194/acp-20-10193-2020 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. https://doi.org/https://doi.org/10.1016/S0048-9697(98)00407-0 Chow, J. C., Lowenthal, D. H., Chen, L. W. A., Wang, X., & Watson, J. G. (2015). Mass reconstruction methods for PM2.5: a review. Air Quality, Atmosphere & Health, 8(3), 243-263. https://doi.org/10.1007/s11869-015-0338-3 Chu-Van, T., Surawski, N., Ristovski, Z., Yuan, C.-S., Stevanovic, S., Rahman, S. A., Hossain, F. M., Guo, Y., Rainey, T., & Brown, R. J. (2020). The effect of diesel fuel sulphur and vanadium on engine performance and emissions. Fuel, 261, 116437. https://doi.org/https://doi.org/10.1016/j.fuel.2019.116437 Corbin, J. C., Mensah, A. A., Pieber, S. M., Orasche, J., Michalke, B., Zanatta, M., Czech, H., Massabò, D., Buatier de Mongeot, F., Mennucci, C., El Haddad, I., Kumar, N. K., Stengel, B., Huang, Y., Zimmermann, R., Prévôt, A. S. H., & Gysel, M. (2018). Trace Metals in Soot and PM2.5 from Heavy-Fuel-Oil Combustion in a Marine Engine. Environmental science & technology, 52(11), 6714-6722. https://doi.org/10.1021/acs.est.8b01764 Fadnavis, S., Roy, C., Chattopadhyay, R., Sioris, C. E., Rap, A., Müller, R., Kumar, K. R., & Krishnan, R. (2018). Transport of trace gases via eddy shedding from the Asian summer monsoon anticyclone and associated impacts on ozone heating rates. Atmos. Chem. Phys., 18(15), 11493-11506. https://doi.org/10.5194/acp-18-11493-2018 Gao, M., Yang, Y., Liao, H., Zhu, B., Zhang, Y., Liu, Z., Lu, X., Wang, C., Zhou, Q., Wang, Y., Zhang, Q., Carmichael, G. R., & Hu, J. (2021). Reduced light absorption of black carbon (BC) and its influence on BC-boundary-layer interactions during “APEC Blue”. Atmos. Chem. Phys., 21(14), 11405-11421. https://doi.org/10.5194/acp-21-11405-2021 Gilbert, R. O. (1987). Statistical methods for environmental pollution monitoring. John Wiley & Sons. Gocic, M., & Trajkovic, S. (2013). Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia. Global and Planetary Change, 100, 172-182. https://doi.org/https://doi.org/10.1016/j.gloplacha.2012.10.014 Grange, S. K., & Carslaw, D. C. (2019). Using meteorological normalisation to detect interventions in air quality time series. Science of The Total Environment, 653, 578-588. https://doi.org/https://doi.org/10.1016/j.scitotenv.2018.10.344 Hien, P. D., Bac, V. T., Thinh, N. T. H., Anh, H. L., Thang, D. D., & Nghia, N. T. (2021). A Comparison Study of Chemical Compositions and Sources of PM1.0 and PM2.5 in Hanoi. Aerosol and Air Quality Research, 21(10), 210056. https://doi.org/10.4209/aaqr.210056 Hu, S., Zhao, G., Tan, T., Li, C., Zong, T., Xu, N., Zhu, W., & Hu, M. (2021). Current challenges of improving visibility due to increasing nitrate fraction in PM2.5 during the haze days in Beijing, China. Environmental Pollution, 290, 118032. https://doi.org/10.1016/j.envpol.2021.118032 Hyslop, N. P. (2009). Impaired visibility: the air pollution people see. Atmospheric Environment, 43(1), 182-195. https://doi.org/https://doi.org/10.1016/j.atmosenv.2008.09.067 Janhäll, S., M. Jonsson, Å., Molnár, P., A. Svensson, E., & Hallquist, M. (2004). Size resolved traffic emission factors of submicrometer particles. Atmospheric Environment, 38(26), 4331-4340. https://doi.org/https://doi.org/10.1016/j.atmosenv.2004.04.018 Jones, A. M., & Harrison, R. M. (2005). Interpretation of particulate elemental and organic carbon concentrations at rural, urban and kerbside sites. Atmospheric Environment, 39(37), 7114-7126. https://doi.org/https://doi.org/10.1016/j.atmosenv.2005.08.017 Kalkavouras, P., Grivas, G., Stavroulas, I., Petrinoli, K., Bougiatioti, A., Liakakou, E., Gerasopoulos, E., & Mihalopoulos, N. (2024). Source apportionment of fine and ultrafine particle number concentrations in a major city of the Eastern Mediterranean. Science of The Total Environment, 915, 170042. https://doi.org/https://doi.org/10.1016/j.scitotenv.2024.170042 Kong, L., Feng, M., Liu, Y., Zhang, Y., Zhang, C., Li, C., Qu, Y., An, J., Liu, X., & Tan, Q. (2020). Elucidating the pollution characteristics of nitrate, sulfate and ammonium in PM2.5 in Chengdu, southwest China, based on 3-year measurements. Atmospheric Chemistry and Physics, 20(19), 11181-11199. https://doi.org/10.5194/acp-20-11181-2020 Li, L., Lei, Y., Wu, S., Chen, J., & Yan, D. (2017). The health economic loss of fine particulate matter (PM2.5) in Beijing. Journal of Cleaner Production, 161, 1153-1161. https://doi.org/https://doi.org/10.1016/j.jclepro.2017.05.029 Lin, Wang, Y., Zheng, F., Zhou, Y., Guo, Y., Feng, Z., Li, C., Zhang, Y., Hakala, S., & Chan, T. (2021). Rapid mass growth and enhanced light extinction of atmospheric aerosols during the heating season haze episodes in Beijing revealed by aerosol–chemistry–radiation–boundary layer interaction. Atmos. Chem. Phys., 21(16), 12173-12187. https://doi.org/https://doi.org/10.5194/acp-21-12173-2021 Lin, Y.-T., Shih, H., Jung, C.-R., Wang, C.-M., Chang, Y.-C., Hsieh, C.-Y., & Hwang, B.-F. (2021). Effect of exposure to fine particulate matter during pregnancy and infancy on paediatric allergic rhinitis. Thorax, 76(6), 568-574. https://doi.org/10.1136/thoraxjnl-2020-215025 Liu, J., Ren, C., Huang, X., Nie, W., Wang, J., Sun, P., Chi, X., & Ding, A. (2020). Increased aerosol extinction efficiency hinders visibility improvement in eastern China. Geophysical Research Letters, 47(20), e2020GL090167. https://doi.org/ https://doi.org/10.1029/2020GL090167 Liu, L., Kuang, Y., Zhai, M., Xue, B., He, Y., Tao, J., Luo, B., Xu, W., Tao, J., Yin, C., Li, F., Xu, H., Deng, T., Deng, X., Tan, H., & Shao, M. (2022). Strong light scattering of highly oxygenated organic aerosols impacts significantly on visibility degradation. Atmos. Chem. Phys., 22(11), 7713-7726. https://doi.org/10.5194/acp-22-7713-2022 Liu, Y., Xu, X., Ji, D., He, J., & Wang, Y. (2024). Examining trends and variability of PM2.5-associated organic and elemental carbon in the megacity of Beijing, China: Insight from decadal continuous in-situ hourly observations. Science of The Total Environment, 938, 173331. https://doi.org/https://doi.org/10.1016/j.scitotenv.2024.173331 Lowenthal, D., & Kumar, N. (2006). Light Scattering from Sea-Salt Aerosols at Interagency Monitoring of Protected Visual Environments (IMPROVE) Sites. Journal of the Air & Waste Management Association, 56(5), 636-642. https://doi.org/10.1080/10473289.2006.10464478 Lu, F., Xu, D., Cheng, Y., Dong, S., Guo, C., Jiang, X., & Zheng, X. (2015). Systematic review and meta-analysis of the adverse health effects of ambient PM2.5 and PM10 pollution in the Chinese population. Environmental research, 136, 196-204. https://doi.org/10.1016/j.envres.2014.06.029 Luo, L., Bai, X., Liu, S., Wu, B., Liu, W., Lv, Y., Guo, Z., Lin, S., Zhao, S., Hao, Y., Hao, J., Zhang, K., Zheng, A., & Tian, H. (2022). Fine particulate matter (PM2.5/PM1.0) in Beijing, China: Variations and chemical compositions as well as sources. Journal of Environmental Sciences, 121, 187-198. https://doi.org/10.1016/j.jes.2021.12.014 Maciejczyk, P., Chen, L.-C., & Thurston, G. (2021). The role of fossil fuel combustion metals in PM2.5 air pollution health associations. Atmosphere, 12(9), 1086. https://doi.org/https://doi.org/10.3390/atmos12091086 Malm, W. C., & Hand, J. L. (2007). An examination of the physical and optical properties of aerosols collected in the IMPROVE program. Atmospheric Environment, 41(16), 3407-3427. https://doi.org/https://doi.org/10.1016/j.atmosenv.2006.12.012 Masiol, M., Agostinelli, C., Formenton, G., Tarabotti, E., & Pavoni, B. (2014). Thirteen years of air pollution hourly monitoring in a large city: Potential sources, trends, cycles and effects of car-free days. Science of The Total Environment, 494-495, 84-96. https://doi.org/https://doi.org/10.1016/j.scitotenv.2014.06.122 Mor, S., Singh, T., Bishnoi, N. R., Bhukal, S., & Ravindra, K. (2022). Understanding seasonal variation in ambient air quality and its relationship with crop residue burning activities in an agrarian state of India. Environmental Science and Pollution Research, 29(3), 4145-4158. https://doi.org/10.1007/s11356-021-15631-6 Pai, S. J., Carter, T. S., Heald, C. L., & Kroll, J. H. (2022). Updated World Health Organization Air Quality Guidelines Highlight the Importance of Non-anthropogenic PM2.5. Environmental Science & Technology Letters, 9(6), 501-506. https://doi.org/10.1021/acs.estlett.2c00203 Pilinis, C., & Farber, R. J. (1991). Evaluation of the Effects of Emission Reductions on Secondary Particulate Matter in the South Coast Air Basin of California. Journal of the Air & Waste Management Association, 41(5), 702-709. https://doi.org/10.1080/10473289.1991.10466870 Pitchford, M., Malm, W., Schichtel, B., Kumar, N., Lowenthal, D., & Hand, J. (2007). Revised algorithm for estimating light extinction from IMPROVE particle speciation data. Journal of the Air & Waste Management Association, 57(11), 1326-1336. https://doi.org/https://doi.org/10.3155/1047-3289.57.11.1326 Room, S. A., Chiu, Y. C., Pan, S. Y., Chen, Y.-C., Hsiao, T.-C., Chou, C. C. K., Hussain, M., & Chi, K. H. (2024). A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown. Environmental Science and Pollution Research, 31(21), 31511-31523. https://doi.org/10.1007/s11356-024-33174-4 Seinfeld, J. H., & Pandis, S. N. (2006). Atmospheric Chemistry and Physics Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American statistical association, 63(324), 1379-1389. https://doi.org/https://doi.org/10.2307/2285891 Shelton, S., Liyanage, G., Jayasekara, S., Pushpawela, B., Rathnayake, U., Jayasundara, A., & Jayasooriya, L. D. (2022). Seasonal variability of air pollutants and their relationships to meteorological parameters in an urban environment. Advances in Meteorology, 2022(1), 5628911. https://doi.org/ https://doi.org/10.1155/2022/5628911 Stocker, T. (2014). Climate change 2013: the physical science basis: Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge university press. https://doi.org/https://doi.org/10.1017/CBO9781107415324 Sun, P., Nie, W., Chi, X., Xie, Y., Huang, X., Xu, Z., Qi, X., Xu, Z., Wang, L., & Wang, T. (2018). Two years of online measurement of fine particulate nitrate in the western Yangtze River Delta: influences of thermodynamics and N2O5 hydrolysis. Atmos. Chem. Phys., 18(23), 17177-17190. https://doi.org/https://doi.org/10.5194/acp-18-17177-2018 Sun, Y., He, Y., Kuang, Y., Xu, W., Song, S., Ma, N., Tao, J., Cheng, P., Wu, C., & Su, H. (2020). Chemical differences between PM1 and PM2.5 in highly polluted environment and implications in air pollution studies. Geophysical Research Letters, 47(5), e2019GL086288. Sun, Y., Zhou, X., & Wang, W. (2016). Aerosol size distributions during haze episodes in winter in Jinan, China. Particuology, 28, 77-85. https://doi.org/https://doi.org/10.1016/j.partic.2015.12.001 Tang, R., Wu, Z., Li, X., Wang, Y., Shang, D., Xiao, Y., Li, M., Zeng, L., Wu, Z., Hallquist, M., Hu, M., & Guo, S. (2018). Primary and secondary organic aerosols in summer 2016 in Beijing. Atmos. Chem. Phys., 18(6), 4055-4068. https://doi.org/10.5194/acp-18-4055-2018 Tao, J., Zhang, L., Cao, J., & Zhang, R. (2017). A review of current knowledge concerning PM2. 5 chemical composition, aerosol optical properties and their relationships across China. Atmos. Chem. Phys., 17(15), 9485-9518. https://doi.org/10.5194/acp-17-9485-2017 Tao, J., Zhang, Z., Wu, Y., Zhang, L., Wu, Z., Cheng, P., Li, M., Chen, L., Zhang, R., & Cao, J. (2019). Impact of particle number and mass size distributions of major chemical components on particle mass scattering efficiency in urban Guangzhou in southern China. Atmos. Chem. Phys., 19(13), 8471-8490. https://doi.org/10.5194/acp-19-8471-2019 Thanh, N. T. K., Maclean, N., & Mahiddine, S. (2014). Mechanisms of Nucleation and Growth of Nanoparticles in Solution. Chemical Reviews, 114(15), 7610-7630. https://doi.org/10.1021/cr400544s Theil, H. (1950). A rank-invariant method of linear and polynomial regression analysis. Indagationes mathematicae, 12(85), 173. Ting, Y.-C., Young, L.-H., Lin, T.-H., Tsay, S.-C., Chang, K.-E., & Hsiao, T.-C. (2022). Quantifying the impacts of PM2.5 constituents and relative humidity on visibility impairment in a suburban area of eastern Asia using long-term in-situ measurements. Science of The Total Environment, 818, 151759. https://doi.org/https://doi.org/10.1016/j.scitotenv.2021.151759 Turpin, B. J., & Huntzicker, J. J. (1991). Secondary formation of organic aerosol in the Los Angeles basin: A descriptive analysis of organic and elemental carbon concentrations. Atmospheric Environment. Part A. General Topics, 25(2), 207-215. https://doi.org/https://doi.org/10.1016/0960-1686(91)90291-E Wang, X., Wang, W., Yang, L., Gao, X., Nie, W., Yu, Y., Xu, P., Zhou, Y., & Wang, Z. (2012). The secondary formation of inorganic aerosols in the droplet mode through heterogeneous aqueous reactions under haze conditions. Atmospheric Environment, 63, 68-76. https://doi.org/https://doi.org/10.1016/j.atmosenv.2012.09.029 WHO. (2021). New WHO Global Air Quality Guidelines aim to save millions of lives from air pollution. https://www.who.int/news/item/22-09-2021-new-who-global-air-quality-guidelines-aim-to-save-millions-of-lives-from-air-pollution Wiedensohler, A., Cheng, Y., Nowak, A., Wehner, B., Achtert, P., Berghof, M., Birmili, W., Wu, Z., Hu, M., & Zhu, T. (2009). Rapid aerosol particle growth and increase of cloud condensation nucleus activity by secondary aerosol formation and condensation: A case study for regional air pollution in northeastern China. Journal of Geophysical Research: Atmospheres, 114(D2). https://doi.org/ https://doi.org/10.1029/2008JD010884 Wu, C., & Yu, J. Z. (2016). 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., 16(8), 5453-5465. https://doi.org/10.5194/acp-16-5453-2016 Wu, T., & Boor, B. E. (2021). Urban aerosol size distributions: a global perspective. Atmos. Chem. Phys., 21(11), 8883-8914. https://doi.org/10.5194/acp-21-8883-2021 Yeh, J. F. (2023). Sources Apportionment of Atmospheric Visibility Degradation in Central Taiwan: From the perspective of particle size distribution National Taiwan University]. Young, L.-H., Hsiao, T.-C., Griffith, S. M., Huang, Y.-H., Hsieh, H.-G., Lin, T.-H., Tsay, S.-C., Lin, Y.-J., Lai, K.-L., Lin, N.-H., & Lin, W.-Y. (2022). Secondary inorganic aerosol chemistry and its impact on atmospheric visibility over an ammonia-rich urban area in Central Taiwan. Environmental Pollution, 312, 119951. https://doi.org/https://doi.org/10.1016/j.envpol.2022.119951 Young, L.-H., Hsu, C.-S., Hsiao, T.-C., Lin, N.-H., Tsay, S.-C., Lin, T.-H., Lin, W.-Y., & Jung, C.-R. (2023). Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan. Science of The Total Environment, 856, 159070. https://doi.org/https://doi.org/10.1016/j.scitotenv.2022.159070 Yuan, C.-S., Lee, C.-G., Liu, S.-H., Chang, J.-c., Yuan, C., & Yang, H.-Y. (2006). Correlation of atmospheric visibility with chemical composition of Kaohsiung aerosols. Atmospheric Research, 82(3-4), 663-679. https://doi.org/https://doi.org/10.1016/j.atmosres.2006.02.027 Zhang, Y., Zhang, Q., Cheng, Y., Su, H., Li, H., Li, M., Zhang, X., Ding, A., & He, K. (2018). Amplification of light absorption of black carbon associated with air pollution. Atmos. Chem. Phys., 18(13), 9879-9896. https://doi.org/10.5194/acp-18-9879-2018 Zheng, H., Kong, S., Zheng, M., Yan, Y., Yao, L., Zheng, S., Yan, Q., Wu, J., Cheng, Y., Chen, N., Bai, Y., Zhao, T., Liu, D., Zhao, D., & Qi, S. (2020). A 5.5-year observations of black carbon aerosol at a megacity in Central China: Levels, sources, and variation trends. Atmospheric Environment, 232, 117581. https://doi.org/https://doi.org/10.1016/j.atmosenv.2020.117581 Zhou, S., Wu, L., Guo, J., Chen, W., Wang, X., Zhao, J., Cheng, Y., Huang, Z., Zhang, J., Sun, Y., Fu, P., Jia, S., Tao, J., Chen, Y., & Kuang, J. (2020). Measurement report: Vertical distribution of atmospheric particulate matter within the urban boundary layer in southern China – size-segregated chemical composition and secondary formation through cloud processing and heterogeneous reactions. Atmos. Chem. Phys., 20(11), 6435-6453. https://doi.org/10.5194/acp-20-6435-2020 | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96987 | - |
dc.description.abstract | 大氣氣膠,特別是粒徑小於2.5微米的細懸浮微粒 (PM2.5) 和小於1微米的微粒 (PM1.0),在空氣污染、氣候變遷及人類健康影響等方面備受關注,並對能見度的降低具有顯著影響。本研究聚焦於臺中地區,探討PM2.5與PM1.0的長期變化趨勢,分析其化學組成、粒徑分佈及光學特性對能見度的影響。研究採用高時間解析度的觀測數據,分析消光係數、散射係數及吸收係數的趨勢,並結合修正的IMPROVE公式與Theil-Sen方法進行統計分析。
研究結果顯示,五年半的觀測期間,消光係數自 106 1/Mm 下降至 66.7 1/Mm(-37.1%),能見度提升約5.6公里。PM2.5濃度每年顯著下降1.74 μg/m³,其中硫酸銨 (Ammonium Sulfate, AS) 每年減少1.01 μg/m³,對消光係數的貢獻每年下降4.08 Mm⁻¹,可能與船舶燃料減排有關。硝酸銨 (Ammonium Nitrate, AN)、黑碳 (Elemental Carbon, EC) 和有機物質(Organic Matter, OM) 所造成的消光係數亦分別每年減少2.56、1.92和1.73 Mm-1,但OM的相對貢獻比例每年上升3.39%,可能成為未來減排的重點。PM2.5的減少主要集中於1.0–2.5 μm範圍,而PM1.0未呈現顯著下降,顯示需進一步探討其形成機制及排放來源,以促進能見度的進一步改善。 此外,能見度良好的乾淨期每年增加3.64%,而能見度劣化事件的發生頻率每年下降1.42%。在劣化事件期間,PM2.5濃度每年下降3.67 μg/m³,AS、AN、EC和OM對消光係數的貢獻分別每年下降7.19、6.34、3.29和2.08 Mm-1,改善幅度高於常態時期。然而,PM1.0在劣化事件期間依然未顯示下降趨勢。粒徑分佈分析顯示,積聚模態 (100–1000 nm) 內的表面積與體積濃度增加,而1.0–2.5 μm範圍則呈現下降,表明化學物種濃度的減少在此範圍內更為顯著。此外,秋冬季粗顆粒比例較高,顯示該季節易受粗顆粒影響,進一步導致能見度劣化事件的發生。 | zh_TW |
dc.description.abstract | Atmospheric aerosols, especially particulate matter with diameters less than 2.5 μm (PM2.5) and 1 μm (PM1.0), are a critical focus of research due to their significant impact on air pollution, climate change, and human health, as well as their significant contribution to visibility degradation. This study investigates the long-term variations of PM2.5 and PM1.0 in the Taichung region, analyzing their chemical composition, particle size distribution, and optical properties in relation to visibility. High temporal resolution observations were used to investigate trends in extinction, scattering, and absorption coefficients, combined with statistical analysis using a revised IMPROVE equation and the Theil-Sen method.
The results show that the extinction coefficient decreased from 106 ± 62.2 1/Mm to 66.7 ± 50.8 1/Mm (-37.1%) over a period of five-and-a-half years, corresponding to an approximate visibility improvement of 5.6 km. PM2.5 concentrations decreased significantly by 1.74 μg/m³ per year, with ammonium sulfate (AS) showing the largest decrease of 1.01 μg/m³ per year, contributing to an annual decrease in the extinction coefficient of 4.08 Mm-1. This trend is likely to be related to reductions in marine fuel emissions. Ammonium nitrate (AN), elemental carbon (EC), and organic matter (OM) also contributed to annual decreases in the extinction coefficient by 2.56, 1.92, and 1.73 Mm⁻¹, respectively. However, the relative contribution of OM to the extinction coefficient increased by 3.39% per year, highlighting its potential as a key focus for future emission reduction strategies. The reduction in PM2.5 was mainly concentrated in the 1.0-2.5 μm range, with no significant reduction observed for PM1.0, indicating the need for further investigation of its formation processes and emission sources to achieve further visibility improvements. In addition, the frequency of clean periods with good visibility increased by 3.64% per year, while the frequency of visibility degradation events decreased by 1.42% per year. During these degradation events, PM2.5 concentrations decreased significantly by 3.67 μg/m³ per year, with AS, AN, EC, and OM contributing to the annual reduction in extinction coefficient by 7.19, 6.34, 3.29, and 2.08 Mm-1, respectively, representing greater improvement rates than during normal periods. However, PM1.0 showed no decreasing trend during the degradation events. Particle size distribution analysis showed increased surface area and volume concentrations within the accumulation mode (100-1000 nm), while concentrations in the 1.0-2.5 μm range decreased, suggesting a more pronounced reduction in chemical species concentrations within this size range. In addition, the higher proportion of coarse particles (>1 μm) during autumn and winter suggests a seasonal susceptibility to coarse particle influence contributing to visibility degradation events. | en |
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dc.description.provenance | Made available in DSpace on 2025-02-25T16:21:49Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 論文口試委員審定書 I
誌謝 II 摘要 III ABSTRACT IV CONTENTS VI LIST OF FIGURES VII LIST OF TABLES XI LIST OF ABBREVIATIONS XIII Chapter 1 Introduction 1 Chapter 2 Methodology 5 2.1 Sampling Site and Instrumentation 5 2.2 Classification 9 2.2.1 Season Classification 9 2.2.2 Visibility Classification 10 2.3 Data Analysis 10 2.3.1 PM2.5 Reconstruction 10 2.3.2 Estimation of Secondary Organic Carbon 12 2.3.3 Revised IMPROVE Algorithm 13 2.3.4 Statistical Analysis of the Trends 15 Chapter 3 Results and Discussion 17 3.1 Measurement Overview 17 3.1.1 Long-Term and Seasonal Trends in Extinction Coefficients and Fine Particulates 17 3.1.2 PM2.5 Chemical Compositions 27 3.1.3 Particle Size Distribution (PSD) 33 3.2 Visibility Degradation Event 38 3.2.1 Event Frequency 38 3.2.2 Particulate Matter and Chemical Composition 40 3.2.3 Particle Size Distribution 51 Chapter 4 Conclusions 57 REFERENCE 59 SUPPLEMENT INFORMATION 65 口試委員意見回覆 78 | - |
dc.language.iso | en | - |
dc.title | 台灣中部能見度與細懸浮微粒物化特性之長期趨勢分析 | zh_TW |
dc.title | Long-Term Trend Analysis of Visibility and the Physicochemical Characteristics of Fine Particulate Matter in Central Taiwan | en |
dc.type | Thesis | - |
dc.date.schoolyear | 113-1 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 楊禮豪;林文印;林能暉 | zh_TW |
dc.contributor.oralexamcommittee | Li-Hao Young;Wen-Yinn Lin;Neng-Huei Lin | en |
dc.subject.keyword | 長期趨勢分析,消光係數,細懸浮微粒,化學組成,微粒粒徑分布, | zh_TW |
dc.subject.keyword | Long-term trend analysis,extinction coefficient,fine particulate matter,chemical composition,particle size distribution, | en |
dc.relation.page | 83 | - |
dc.identifier.doi | 10.6342/NTU202500505 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2025-02-10 | - |
dc.contributor.author-college | 工學院 | - |
dc.contributor.author-dept | 環境工程學研究所 | - |
dc.date.embargo-lift | 2030-02-08 | - |
顯示於系所單位: | 環境工程學研究所 |
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