都市CO2的過量排放，是造成全球氣候暖化與環境變異的主因之一。低碳都市的發展成為目前永續發展的核心議題，亦是抑制氣候暖化的關鍵。低碳都市的概念，包括空間和非空間維度。空間維度探討了都市型態、土地利用與運輸系統，非空間維度則著眼於經濟、能源使用和節能產品。然而過去低碳方面的研究，多聚焦於非空間維度之探討上，甚少關注空間維度面向，但面對全球氣候暖化與低碳發展，都市不僅可落實低碳發展政策，其規劃更在低碳都市的建設與發展過程中扮演關鍵角色。因此，本研究依循「全球考量，在地行動」之概念及方式，以低碳都市為主軸，並以空間規劃及環境經濟之角度切入，針對低碳都市衡量指標建構及分析、縣市低碳效率評估及低碳政策影響效果之探討、都市發展及空間結構與碳量間關係之探討等三項研究主題，進行實證分析與探討，企圖補強低碳都市在空間維度之論述，使都市的低碳化有所依循，亦使都市能藉此更達低碳與永續之目標。 在「低碳都市衡量指標系統之建構及探討」主題上，以台灣為實證案例，根據低碳都市的內涵、理念與目標，研撰適宜之衡量指標系統，透過因子分析定權法進行衡量指標的擇取，藉此評估台灣各縣市的低碳發展狀態。根據實證結果，顯示台灣的低碳都市評估指標系統，包括「環境品質及資源消耗」、「經濟及建設」、「財政及資源循環」、「社會狀態」等4構面，共22個指標；而台灣各縣市在低碳發展的綜合表現上，以台北市的狀態最佳，而以彰化縣表現最差。 而在「縣市低碳發展效率評估及低碳政策影響效果之探討」主題上，以台灣各縣市作為實證案例，在考量非意欲產出下(碳排放威脅、環境污染衝擊)，透過DEA中的不良產出模型(Bad Outputs Model)評估縣市低碳發展效率，並藉由Tobit模型，釐清低碳政策對縣市低碳發展效率之影響效果。依據不良產出模型之效率評估結果，顯示臺北市、新竹市、臺東縣、花蓮縣在低碳發展效率上相對具有效率，且已達最適規模水準；而高雄縣是目前亟待改善的首要縣市。此外，藉由Tobit模式的實證分析，其結果顯示工廠家數、資源回收量、市區公車系統路線總長、具綠建築標章的建物數、綠地面積等變數，對縣市低碳發展效率有顯著影響，其中，除工廠家數對縣市低碳發展效率有負向影響外，其餘變數皆呈正向影響效果。而由此亦得知產業結構、資源循環利用、低碳運輸、低碳建築、碳匯規劃等低碳政策，對於縣市低碳發展效率是顯著有效的。 在「都市發展及空間結構與碳量關係之探討」主題上，以台灣各縣市作為實證案例，透過偏最小平方法的分析，實證都市發展及空間結構對碳量之影響關係與影響程度，並找出低碳都市發展中關鍵的空間規劃要素。而根據偏最小平方法的實證結果，顯示都市混合度、都市發展強度及密度與都市綠化對碳淨存量產生負向影響，亦即都市混合度、都市緊密度及綠化程度愈高，愈能減少碳淨存量；而都市工業機能、都市交通狀態對碳淨存量有正向影響，亦即都市工業機能與都市交通狀態愈高，愈會增加碳淨存量，其中又以都市交通狀態的影響效果最大。 綜合上述，本研究之研究成果包括：「釐清低碳都市模糊且紛雜的概念及內涵」、「建構適宜台灣本土的低碳都市衡量指標系統」、「評估台灣各縣市低碳發展之整體狀態」、「評估台灣各縣市之低碳發展效率」、「檢視台灣現行低碳政策對於縣市低碳發展效率之影響效果」及「找出低碳都市發展中關鍵的空間規劃要素」，期待此些成果，能作為地方政府或規劃單位於低碳目標下，進行低碳都市發展及規劃開發時之參考。 / Excessive CO2 emission is one of the main causes of causing global warming and climate change. Therefore, low-carbon urban development is currently the core issue in sustainable development, and it is also the key to curb climate warming. The concept of the low-carbon city includes spatial dimension and non-spatial dimension. The former contains the issues of urban form, transportation system, and land use planning, the latter contains the issues of economy, energy consuming, and energy saving product. The spatial dimension plays the important role in the construction and development of the low-carbon city, but only the few studies focused on. Therefore, this paper takes the spatial dimension of the low-carbon city as the main scope, and discusses the topics of “research on low-carbon city indicator system”, “evaluating the low-carbon efficiency of city and analyzing its influential policies”, and “the effects of urban development and spatial structure on carbon emissions”. In the topics of “research on low-carbon city indicator system”, this paper takes cities and counties of Taiwan as the empirical cases, and uses factor analysis to establish the appropriate low-carbon city indicator system for Taiwan. Furthermore, this paper evaluates the cities'/counties' status of low-carbon developments by this low-carbon city indicator system. According to the empirical results, there are four evaluating aspects of the low-carbon city: 1) environmental quality and resource consumption, 2) economy and construction, 3) finance and resource recycling and 4) social status. Based on the comprehensive performance of the low-carbon city indicator system, Taipei City shows the best performance, whereas Changhua County shows the worst performance. In the topics of “evaluating the low-carbon efficiency of the city and analyzing its influential policies”, this paper takes cities and counties of Taiwan as the empirical cases, and assesses low-carbon efficiency of the city by Bad Outputs Model. Moreover, this paper uses Tobit Model to analyze the influence of low-carbon policies on the low-carbon efficiency of the city. According to the result of Bad Outputs Model, Taipei City, Hsinchu City, Taitung County, and Hualien County are efficiency, and achieve the optimal scale level. Moreover, Kaohsiung County is the county in the most urgent need of improvement. Another result of Tobit model indicates that the industrial unit has the negative impact on the low-carbon efficiency of the city. Moreover, resource recovery, the total length of the urban bus route, the number of green buildings, and green area all have the positive impact on the low-carbon efficiency of the city. In the topics of “the effects of urban development and spatial structure on carbon emissions”, this paper takes cities and counties of Taiwan as the empirical cases, and uses partial least squares method (PLS) to identify the impact of urban development and spatial structure on carbon emissions. The empirical results show that the mixed land use, urban intensity and density, and urban greening all have the negative impact on carbon emissions. Moreover, industrial function and urban transportation all have a positive impact on carbon emissions. Finally, these results can be used as reference for future low-carbon urban planning and policy.