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能源消耗.污染排放與車輛使用之整合關聯模式研究(2/3)的圖書 |
能源消耗、污染排放與車輛使用之整合關聯模式研究(2/3) 作者:陳一昌等 出版社:交通部運輸研究所 出版日期:2009-03-01 語言:繁體中文 規格:平裝 / 493頁 / 8k / 普級 / 單色印刷 / 初版 |
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本研究旨在建構能源消耗、污染排放與車輛使用之整合關聯模式,俾進一步評估及預測各種汽機車管理策略對能源消耗與污染排放之減量效果。為達此一目的,本計畫利用上一年度回收有效問卷5,915份,進行全國型及區域型家戶汽、機車個體選擇模式,包括持有與使用、車型與車齡,以及替代能源車輛選擇等模式。為提高模式應用便利性,本計畫整合各項校估完成之個體選擇模式,設計一套決策支援系統芻型,以供汽機車管理策略研擬與評估之用。此外,為蒐集車輛個體選擇模式之橫縱資料(panel data),藉以掌握汽機車個體動態選擇行為,本年度乃進一步進行追蹤及擴大問卷調查。其中,追蹤問卷總計回收有效問卷2,860份(有效回收率為48.35%)。擴大問卷調查共發放汽機車各20,000份,回收有效問卷4,811份(有效回收率為12.03%)。此資料將供本計畫下一年期動態個體選擇模式建構之基礎。最後,本年度也串聯汽機車定檢資料及問卷調查資料,利用結構方程式建立污染排放整合關聯模式,分析高污染車種類型及其主要使用人特性,以供相關管理策略研究依據。本研究已可預測外在環境及相關政策影響民眾持有及使用汽機車的變化,且有具體量化預估值,可輔助擬定相關管理策略。現有收集之家戶汽機車使用行為資料、模式及參數,亦可供學術界、政府環保及能源部門參考及應用,以提升其模式預測精度及品質。
This project aims to develop an integrated model that correlates vehicle usage with energy consumption and emissions for evaluating the effects of vehicle ownership and/or usage management strategies on the reduction of energy consumption and emissions. In doing so, based on a total of 5,915 valid questionnaire samples surveyed by this project last year, the project respectively developed nationwide and regional disaggregate choice models of cars and motorcycles, including ownership and usage choice model, type and vintage choice model, and alternative-fuel vehicle choice model. To enhance the applicability of the proposed models, this project integrated all these models to develop a prototype decision making system for proposing and evaluating the management strategies of cars and motorcycles. In addition, to collect ownership and usage panel data of cars and motorcycles for capturing dynamic behaviors, this project further carried out a follow-up questionnaire survey and an expanded questionnaire survey (20,000 expanded questionnaires). We collected a total of 2,860 valid returned follow-up samples with a return rate of 48.35% and 4,811 valid returned expanded questionnaire samples with a return rate of 12.03%. These datasets can be used to develop dynamic disaggregate choice models in the next year of this project. At last, this project also combined Motor Vehicle Exhaust Inspection/Management dataset and questionnaire survey dataset, to develop an integrated correlational model for car and motorcycle emissions. The direct key factors (i.e. vehicle characteristics) and indirect factors (i.e. driver demographics, area in use, and vehicle usage) affecting the emissions of cars and motorcycles have been identified along with corresponding management strategies recommended. Obviously, the purposes of this project have been successfully accomplished. The proposed models can be used to facilitate the analysis of the effects of management strategies on the reduction of emissions and energy consumption in the following studies.
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