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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 謝依芸(I-Yun Lisa Hsieh) | |
dc.contributor.advisor | 謝依芸(I-Yun Lisa Hsieh | iyhsieh@ntu.edu.tw | ), | |
dc.contributor.author | Tsung-Heng Chang | en |
dc.contributor.author | 張綜桁 | zh_TW |
dc.date.accessioned | 2023-03-19T23:31:57Z | - |
dc.date.copyright | 2022-09-23 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-09-20 | |
dc.identifier.citation | [1] United Nations Framework Convention on Climate Change (UNFCCC). The Paris Agreement 2020. https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement (accessed June 21, 2022). [2] Keohane. What the next 5 years hold for the Paris Agreement. Climate 411 2020. https://blogs.edf.org/climate411/2020/12/16/what-the-next-5-years-hold-for-the-paris-agreement/ (accessed June 21, 2022). [3] INDC, Executive Yuan. Submission by Republic of China (Taiwan)Intended Nationally Determined Contribution 2015. https://enews.epa.gov.tw/page/3b3c62c78849f32f/f328b652-4540-4a24-94fb-21eb17845f43 (accessed June 21, 2022). [4] National Development Council. Taiwan’s Pathway to Net-Zero Emissions in 2050. Taiwan’s Pathway to Net-Zero Emissions in 2050 2022. https://www.ndc.gov.tw/Content_List.aspx?n=FD76ECBAE77D9811 (accessed June 21, 2022). [5] Environmental Protection Administration. Amendment of Greenhouse Gas Reduction and Management Act. Climate talks 2022. https://www.climatetalks.tw/%E6%BA%AB%E7%AE%A1%E6%B3%95%E4%BF%AE%E6%B3%95-1 (accessed June 21, 2022). [6] Bureau of Energy. Overview of Energy Consumption in 2019. Bureau of Energy, Ministry of Economic Affairs, ROC 2019. https://www.moeaboe.gov.tw/ECW/populace/content/Content.aspx?menu_id=14436 (accessed June 21, 2022). [7] Environmental Protection Administration. TEDS 11.0. 2019. [8] International Council on Clean Transportation. Vision 2050: A Strategy to Decarbonize the Global Transport Sector by Mid-Century. International Council on Clean Transportation 2020. https://theicct.org/publication/vision-2050-a-strategy-to-decarbonize-the-global-transport-sector-by-mid-century/ (accessed June 21, 2022). [9] United Nations Environment Programme. Life Cycle Assessment. 1996. [10] Wang M, Elgowainy A, Benavides PT, Burnham A, Cai H, Dai Q, et al. Summary of Expansions and Updates in GREET® 2018. Argonne National Lab. (ANL), Argonne, IL (United States); 2018. https://doi.org/10.2172/1483843. [11] Dai D, Leng R, Zhang C, Wang C. Using hybrid modeling for life cycle assessment of motor bike and electric bike. J Cent South Univ Technol 2005;12:77–80. https://doi.org/10.1007/s11771-005-0014-0. [12] Huang Y, Jiang L, Chen H, Dave K, Parry T. Comparative life cycle assessment of electric bikes for commuting in the UK. Transportation Research Part D: Transport and Environment 2022;105:103213. https://doi.org/10.1016/j.trd.2022.103213. [13] Nordelöf A, Messagie M, Tillman A-M, Ljunggren Söderman M, Van Mierlo J. Environmental impacts of hybrid, plug-in hybrid, and battery electric vehicles—what can we learn from life cycle assessment? Int J Life Cycle Assess 2014;19:1866–90. https://doi.org/10.1007/s11367-014-0788-0. [14] Marmiroli B, Messagie M, Dotelli G, Van Mierlo J. Electricity Generation in LCA of Electric Vehicles: A Review. Applied Sciences 2018;8:1384. https://doi.org/10.3390/app8081384. [15] Prussi M, Yugo M, De PL, Padella M, Edwards R. JEC Well-To-Wheels report v5. 2020. https://doi.org/10.2760/100379. [16] Liu X, Reddi K, Elgowainy A, Lohse-Busch H, Wang M, Rustagi N. Comparison of well-to-wheels energy use and emissions of a hydrogen fuel cell electric vehicle relative to a conventional gasoline-powered internal combustion engine vehicle. International Journal of Hydrogen Energy 2020;45:972–83. https://doi.org/10.1016/j.ijhydene.2019.10.192. [17] Al-Buenain A, Al-Muhannadi S, Falamarzi M, Kutty AA, Kucukvar M, Onat NC. The Adoption of Electric Vehicles in Qatar Can Contribute to Net Carbon Emission Reduction but Requires Strong Government Incentives. Vehicles 2021;3:618–35. https://doi.org/10.3390/vehicles3030037. [18] Wang M. Argonne GREET Publication : Technical Report: GREET 1.5 -- Transportation Fuel-Cycle Model - Volume 1: Methodology, Development, Use, and Results 1999. https://greet.es.anl.gov/publication-20z8ihl0 (accessed June 21, 2022). [19] Bandivadekar AP. Evaluating the impact of advanced vehicle and fuel technologies in U.S. light duty vehicle fleet. Thesis. Massachusetts Institute of Technology, 2008. [20] Yang C, McCollum D, McCarthy R, Leighty W. Meeting an 80% reduction in greenhouse gas emissions from transportation by 2050: A case study in California. Transportation Research Part D: Transport and Environment 2009;14:147–56. https://doi.org/10.1016/j.trd.2008.11.010. [21] Garcia R, Freire F. A review of fleet-based life-cycle approaches focusing on energy and environmental impacts of vehicles. Renewable and Sustainable Energy Reviews 2017;79:935–45. https://doi.org/10.1016/j.rser.2017.05.145. [22] He K, Huo H, Zhang Q, He D, An F, Wang M, et al. Oil consumption and CO2 emissions in China’s road transport: current status, future trends, and policy implications. Energy Policy 2005;33:1499–507. [23] Wang C, Cai W, Lu X, Chen J. CO2 mitigation scenarios in China’s road transport sector. Energy Conversion and Management 2007;7:2110–8. https://doi.org/10.1016/j.enconman.2006.12.022. [24] Hsieh I-YL, Kishimoto PN, Green WH. Incorporating multiple uncertainties into projections of Chinese private car sales and stock. Prof Green 2018. [25] Huo H, Wang M, Johnson L, He D. Projection of Chinese Motor Vehicle Growth, Oil Demand, and CO2 Emissions Through 2050 - Hong Huo, Michael Wang, Larry Johnson, Dongquan He, 2007 2007. https://journals.sagepub.com/doi/10.3141/2038-09 (accessed June 21, 2022). [26] Huo H, Wang M. Modeling future vehicle sales and stock in China. Energy Policy 2012;43:17–29. [27] Wu T, Zhao H, Ou X. Vehicle Ownership Analysis Based on GDP per Capita in China: 1963–2050. Sustainability 2014;6:4877–99. https://doi.org/10.3390/su6084877. [28] Hao H, Wang H, Yi R. Hybrid modeling of China’s vehicle ownership and projection through 2050. Fuel and Energy Abstracts 2011;36:1351–61. https://doi.org/10.1016/j.energy.2010.10.055. [29] Peng T, Ou X, Yuan Z, Yan X, Zhang X. Development and application of China provincial road transport energy demand and GHG emissions analysis model. Applied Energy 2018;222:313–28. https://doi.org/10.1016/j.apenergy.2018.03.139. [30] CIER, Environmental Protection Administration, Liang C-Y. Life-cycle analysis for Taiwan vehicles. 2016. [31] Chung C-L, Chang C-C. Analysis the benefits of energy conservation in road transport- A case of Taiwan. National Cheng Kung University, 2016. [32] Tanner JC. Car and Motorcycle Ownership in the Counties of Great Britain in 1960. Journal of the Royal Statistical Society Series A (General) 1963;126:276–84. https://doi.org/10.2307/2982370. [33] Lawrence W. Lan, Huang, Yeh-chieh. 我國機車數量成長趨勢預測. 中華民國第二屆機車交通與安全研討會論文集 1998:1–17. [34] Sillaparcharn P. Modeling of Vehicle Ownership: Case Study of Thailand. Transportation Research Record 2007;2038:98–104. https://doi.org/10.3141/2038-13. [35] Cheng C-Y. Forecasting Model for Automobile in Taiwan-Performance Comparison between ARMAX and Artificail Neural Network. Master Thesis. National Cheng Kung University, 2013. [36] Zachariadis T, Samaras Z, Zierock K-H. Dynamic modeling of vehicle populations: An engineering approach for emissions calculations. Technological Forecasting and Social Change 1995;50:135–49. https://doi.org/10.1016/0040-1625(95)00057-H. [37] Hsu T-P. Comparative study on motorcycle ownership forecasting model of Asian Countries-Taiwan, Malaysia and Vietnam. Proceedings the 6th International Conference of Eastern Asia Society for Transpiration Studies 2005;5. [38] Nishitateno S, Burke PJ. The motorcycle Kuznets curve. Journal of Transport Geography 2014;36:116–23. https://doi.org/10.1016/j.jtrangeo.2014.03.008. [39] Chu MY, Law TH, Hamid H, Law SH, Lee JC. Examining the effects of urbanization and purchasing power on the relationship between motorcycle ownership and economic development: A panel data. International Journal of Transportation Science and Technology 2022;11:72–82. https://doi.org/10.1016/j.ijtst.2020.12.004. [40] Jou R-C, Chen C-C, Weng M-C. Relationship between Household Car/Motorbike Ownership and Usage in Taiwan-Applications of the Ordered Bivariate Probit and Sure Models. Transportation Planning Journal 2004;33:625–47. https://doi.org/10.6402/TPJ.200412.0625. [41] Chiang, Yu-sheng, Liao, Jen-che. The Mixed Choice Models of Car Ownership, Use, and Mode to Work Derived from the Same Utility of Household: The Empirical Analysis of Taiwan Area. Transportation Planning Journal 1998;27:4 1998.12. https://doi.org/10.6402/TPJ. [42] Pongthanaisawan J, Sorapipatana C. Relationship between level of economic development and motorcycle and car ownerships and their impacts on fuel consumption and greenhouse gas emission in Thailand. Renewable and Sustainable Energy Reviews 2010;14:2966–75. https://doi.org/10.1016/j.rser.2010.07.034. [43] Directorate General of Budget, Accounting and Statistics. The Survey of Family Income and Expenditure 2020. https://win.dgbas.gov.tw/fies/a11.asp?year=109 (accessed June 21, 2022). [44] Bento A, Roth K, Zuo Y. Vehicle Lifetime Trends and Scrappage Behavior in the U.S. Used Car Market. EJ 2018;39. https://doi.org/10.5547/01956574.39.1.aben. [45] Zheng J, Zhou Y, Yu R, Zhao D, Lu Z, Zhang P. Survival rate of China passenger vehicles: A data-driven approach. Energy Policy 2019;129:587–97. https://doi.org/10.1016/j.enpol.2019.02.037. [46] Ministry of Transportation and Communications. Monthly Statistics of Transportation and Communications 2021. https://www.motc.gov.tw/ch/home.jsp?id=578&parentpath=0%2C6&mcustomize=statistics301.jsp (accessed June 21, 2022). [47] Dargay J, Gately D. Income’s effect on car and vehicle ownership, worldwide: 1960-2015. Transportation Research Part A: Policy and Practice 1999;33:101–38. [48] Huang W-L, Chiou Y-C, Wen C-H. Dynamic Disaggregate Models of Car/Motorcycle Ownership and Usage - a Panel Data Modeling Approach. National Chiao Tung University, 2009. [49] Institute of Transportation, Chang H-L. A Study for the Patterns of Motorcycle Ownership and Usage in Our Country 2001. [50] Hsieh I-YL, Chossière GP, Gençer E, Chen H, Barrett S, Green WH. An Integrated Assessment of Emissions, Air Quality, and Public Health Impacts of China’s Transition to Electric Vehicles. Environ Sci Technol 2022;56:6836–46. https://doi.org/10.1021/acs.est.1c06148. [51] Efron B. Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics 1979;7:1–26. https://doi.org/10.1214/aos/1176344552. [52] Kulesa A, Krzywinski M, Blainey P, Altman N. Sampling distributions and the bootstrap. Nature Methods 2015;12:477–8. https://doi.org/10.1038/nmeth.3414. [53] Wang H, Ou X, Zhang X. Mode, technology, energy consumption, and resulting CO2 emissions in China’s transport sector up to 2050. Energy Policy 2017;109:719–33. https://doi.org/10.1016/j.enpol.2017.07.010. [54] Bureau of Energy M of EA. Monthly issuance of the energy efficiency labels for electric vehicles 2022. [55] Environmental Protection Administration. the regular exhaust inspection records. the regular exhaust inspection records 2021. https://motor.epa.gov.tw/Report/Report_List.aspx (accessed July 11, 2022). [56] Environmental Protection Administration. Greenhouse Gas Emissions Information Platform for Businesses 2020. https://ghgregistry.epa.gov.tw/ghg_rwd/Main/Examine/Examine_2 (accessed July 11, 2022). [57] Taiwan Power Company. Annual report of Taipower. 2020. [58] Institute of Transportation. A life cycle analysis of domestic alternative fuel vehicles regarding energy consumption and greenhouse gas emissions. 2013. [59] European Environment Agency. Greenhouse gas emission intensity of electricity generation in Europe 2021. https://www.eea.europa.eu/ims/greenhouse-gas-emission-intensity-of-1 (accessed July 11, 2022). [60] Bureau of Energy M of EA. IPP fire power station 2020. https://www.moeaboe.gov.tw/ECW/populace/content/Content.aspx?menu_id=999 (accessed July 11, 2022). [61] Taiwan Power Company. Long-term power development planning 2021. https://www.taipower.com.tw/tc/page.aspx?mid=212&cid=122&cchk=260a432c-fc0e-47e0-a90e-2bc0cc52cb61 (accessed July 11, 2022). | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85992 | - |
dc.description.abstract | 為衡量2050淨零排放目標下機車於運輸部門之減碳成果,本研究建立一個包含機車持有預測、以及以燃料生命週期為基礎的能源需求與溫室氣體排放模型。在機車持有方面,過去的研究指出機車無法使用傳統常用來描述汽車擁有數的S型曲線來呈現;取而代之,隨著所得增加,機車的持有反而呈現U型反轉的情況。本論文提出以Gamma分布函數為基礎的機車持有率模型,發現加入常數項的模型在數學上更能詮釋台灣的機車持有機率,暗示機車持有在我國具有基本的需求。研究中也引入拔靴法用以評估模型參數本身的不確定性,進而呈現機車持有(率)數、能源需求、溫室氣體排放預測的信賴區間。本研究指出,全國機車持有率將於2035年達到每100人持有59.15輛的高峰,接著U型反轉下降至2050年達每100人58.72輛。然而全國人口的急遽下降,使機車持有數將於2024年提前達到高峰,約13.82百萬輛,並於2050年達約11.96百萬輛。另外,燃油與電動機車每公里的燃油生命週期(即油井到輪子階段;WTW)溫室氣體排放,是以本研究的GREET-Taiwan模型以及電網排碳係數推估結果,作為後續推估整體排放的基礎。本研究設計三種情境,分別是基準情境(BASE)、推行電動機車情境(ESC)、推行電動機車以及電網改善情境(ESC-GRID),採用從油井到輪子(WTW)分析法來衡量2050淨零排放政策規劃下是否能有效達到所設定目標,並了解各情境的減碳成果。研究發現,在2050年,ESC-GRID情境的生命週期排放將會降至1.37 百萬公噸,且該情境2020至2050的累積生命週期溫室氣體排放量約188百萬公噸—低於ESC情境的196百萬公噸以及BASE情境的265百萬公噸。在2050淨零排放政策下(2040年機車銷售全面電動化),電動機車在2050年佔整體機車將達約85%(即燃油機車佔約15%),卻仍將造成0.91百萬公噸的溫室氣體直接排放,高於政策所預期的0.41百萬公噸。但若2050年電動機車保有量佔比達93.3%,或是機車每年平均行駛里程降低55%,則該目標將有機會達成。綜上所述,本研究由下而上開發的機車車輛至生命週期的能源消耗與溫室氣體排放模型,將有助於我國未來評估車輛電動化以及能源轉型政策。 | zh_TW |
dc.description.abstract | Taiwan has recently published“Taiwan’s Pathway to Net-Zero Emissions in 2050” with a clear timeline for vehicle electrification. With the world's highest density of two-wheeler ownership highest density of two-wheeler ownership in the world, Taiwan’s scooter fleet turnover should be carefully studied for understanding long-term fleet trends and greenhouse gas (GHG) emissions under various policies. This thesis, therefore, develops a bottom-up model for Taiwan’s scooter fleet to examine scooter fleet turnover pace, future energy demand, and GHG emissions from a life cycle perspective. Based on the household survey data, it is found that the propensity to own a scooter would grow during the beginning stages as the income increases; but instead of approaching a saturation level like private cars, scooter ownership would start declining once a threshold level is exceeded. Consequently, this thesis proposes using Gamma distribution (i.e., inverse U shape) to simulate scooter ownership patterns. After adding a constant term to the gamma distribution, the mathematical model gives the better curve fitting (R2 = 0.83) results, suggesting that scooters are widely considered a necessity in Taiwan. Moreover, the bootstrap method is adopted to characterize this inherent uncertainty and establish the confidence intervals for vehicle stock forecasting. The model results indicate that Taiwan’s scooter stock will reach the peak at 13.82 million (95% CI: 13.58 – 13.96 million) around 2024 and then decrease to 11.96 million (95% CI: 11.54 – 12.15 million) in 2050. Scenario analysis is conducted to explore the potential GHG emissions reduction by scooter electrification alone and the deployment synergy between electric scooters and the decarbonization in power sector. Under the 2050 Net-Zero Pathway (i.e., ESC-GRID scenario; electric scooters with cleaner power grid), the battery-powered scooters will account for nearly 85% of the scooter stock by 2050, and the direct (i.e., pump-to-wheel; PTW) carbon emission will be 0.91 Mt per year, which is still 0.5 Mt more than the net-zero emissions target for scooters. Based on the scooter fleet model, as long as 93.3% of the on-road scooters are electric in 2050, the decarbonization target could be achieved. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T23:31:57Z (GMT). No. of bitstreams: 1 U0001-1509202213252300.pdf: 2854826 bytes, checksum: 9e363d708ca51b52337b458707ff2dc8 (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 口試委員會審定書 i 誌謝 ii 中文摘要 iv Abstract v Table of Contents vi Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivation and Research Gap 2 Chapter 2 Literature Review 4 2.1 Life-cycle assessment and Well-to-Wheel analysis 4 2.2 Vehicle fleet model 6 2.2.1 Four-wheeled vehicles fleet model 6 2.2.2 Scooter fleet model 7 Chapter 3 Methods and Data 9 3.1 Overview of the Thesis and Scooter Fleet Model Framework 9 3.1.1 Research Scope 9 3.1.2 Overview of the Model Framework 10 3.2 Scooter Modules 12 3.2.1 Stock and Sales 12 3.2.2 Disposable Income Distribution (I) 15 3.2.3 Ownership probability function ( γ) 17 3.3 Bootstrap Confidence Intervals 20 3.4 Energy Demand and GHG Emissions Modules 21 3.4.1 Results of Energy intensities and Grid Intensities 22 3.4.2 Details for Projection of Grid carbon Intensities 23 3.5 Scenario Design for 2050 Net-Zero Pathway 26 Chapter 4 Results and Discussion 28 4.1 Scooter Stock and Sales Projection of National level and County level 28 4.2 Life-cycle Energy Demand and GHG Emissions Under Different Scenarios 36 4.3 Impacts of Decarbonization Pathways on Life-cycle GHG Emissions 42 4.4 Changes in PTW emissions under different degrees of VKT reduction 44 Chapter 5 Conclusion 45 5.1 Findings 45 5.2 Suggestions 46 Reference 48 | |
dc.language.iso | en | |
dc.title | 邁向公路淨零排放:臺灣機車車隊模型發展與應用 | zh_TW |
dc.title | Towards Net-Zero Road Transport: Taiwan Scooter Fleet Model Development and Application | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 汪立本(Li-Pen Wang),張學孔(Shyue-Koong Jason Chang),林心恬(Hsin-Tien Lin) | |
dc.subject.keyword | 機車持有,機車電動化,溫室氣體,淨零排放,生命週期分析,拔靴法信賴區間, | zh_TW |
dc.subject.keyword | Scooter,Motorcycle,Scooter electrification,GHG,Net-Zero Emission,Life-cycle analysis,Bootstrap confidence interval, | en |
dc.relation.page | 53 | |
dc.identifier.doi | 10.6342/NTU202203432 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2022-09-21 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
dc.date.embargo-lift | 2024-09-01 | - |
顯示於系所單位: | 土木工程學系 |
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