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題名 低碳都市評估及其空間結構之分析
Evaluating the Efficiency of Low-Carbon City and Analyzing the Effects of Spatial Structure on Carbon Emissions
作者 沈育生
Shen, Yu Sheng
貢獻者 劉小蘭
Liu, Hsiao Lan
沈育生
Shen, Yu Sheng
關鍵詞 低碳都市
指標系統
低碳發展效率
低碳政策
空間結構
碳量
Low-Carbon City
Indicator System
Low-Carbon Efficiency
Low-Carbon Policies
Spatial Structure
Carbon Emissions
日期 2015
上傳時間 27-Jul-2015 11:32:25 (UTC+8)
摘要 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.
參考文獻 1.Anderson, W. P., Kanaroglou, P. S., and Miller, E. J. (1996).Urban form, energy and the environment: A review of issues, evidence and policy, Urban Studies, 33:7-35.
     2.Aragon-Correa, J.A. (1998). Strategic proactivity and firm approach to the natural environment, The Academy of Management Journal, 41(5): 556-567.
     3.Arcelus, F., and Arocena, P.(2005). Productivity differences across OECD countries in the presence of environmental constraints, Journal of the Operational Research Society, 56(12): 1352-1362.
     4.Baeumler, A., Ijjasz-Vasquez, E., and Mehndiratta, S. (2012). Sustainable Low-Carbon City Development in China, New York: World Bank Publications.
     5.Barkalow, G., Bemis, G., McKeever, N., Phinney, S., and Vinton, J. (2007). The Role of Land Use in Meeting California’s Energy and Climate Change Goals, California: California Energy Commission.
     6.Barney, J. B. (1991). Firm resources and sustained competitive advantage, Journal of Management, 17(1): 99-120.
     7.Barter, P.A. (2000). Transport dilemmas in dense urban areas: examples from Eastern Asia. In Compact cities: Sustainable urban forms for developing countries, ed. M. Jenks, and R. Burgess, 271-284. London: E & FN Spon.
     8.Basiago, A. D. (1998). Economic, social, and environmental sustainability in development theory and urban planning practice, Environmentalist, 19(2): 145-161.
     9.Beatley, T. (2000). Green Urbanism: Learning from European Cities, Washington, D.C.: Island Press.
     10.Bella, G., Massidda, C., and Mattana, P. (2014). The relationship among CO2 emissions, electricity power consumption and GDP in OECD countries, Journal of Policy Modeling, 36(6): 970-985.
     11.Bi, J., Zhang, R.R., Wang, H.K., Liu, M.M., and Wu, Y. (2011). The benchmarks of carbon emissions and policy implications for China`s cities: Case of Nanjing, Energy Policy, 39(9): 4785-4794.
     12.Bollen, K. A. (1989). Structural equations with Latent Variables. New York: Wiley.
     13.Boussofiane, A., Dyson, R. G., and Thanassoulis, E. (1991). Applied Data Envelopment Analysis, European Journal of Operational Research, 52: 1-15.
     14.Burton, E. (2002). Measuring urban compactness in UK towns and cities, Environment and Planning B: Planning and Design, 29: 219-250.
     15.Cai, B.F., Wang, J.N., Yang, W.S., Liu, L.C., and Cao, D. (2012). Low carbon society in China: Research and practice, Advances in Climate Change Research, 3(2): 106-120.
     16.Cervero, R. (1996). Mixed land-uses and commuting: Evidence from the American housing survey, Transportation Research Part A: Policy And Practice, 30(5): 361-377.
     17.Cervero, R., and Day, J. (2008).Suburbanization and transit-oriented development in China, Transport Policy, 15(5): 315-323.
     18.Cervero, R., and Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design, Transportation Research Part D: Transport and Environment, 2(3): 99-219.
     19.Chan, H.W., Choy, H.T., and Yung, H.K. (2013). Current research on low-carbon cities and institutional responses, Habitat International, 37: 1-3.
     20.Chang, Y.T., Zhang, N., Danao, D., and Zhang, N.(2013). Environmental efficiency analysis of transportation system in China: A non-radial DEA approach, Energy Policy, 58: 277-283.
     21.Chapman, R. (2008).Transitioning to low-carbon urban form and transport in New Zealand, Political Science, 60(1): 89-98.
     22.Charmondusit, K. And Keartpakpraek K. (2010). Eco-Efficiency Evaluation of the Petroleum and Petrochemical Group in the Map Ta Phut Industrial Estate, Tailand, Journal of Cleaner Production, 19(2-3): 241–252.
     23.Chatham House, Chinese Academy of Social Sciences, Energy Research Institute, Jilin University, E3G. (2010). Low Carbon Development Roadmap for Jilin City, London: Royal Institute of International Affairs.
     24.Chen, F., and Zhu, D. (2013). Theoretical research on low-carbon city and empirical study of Shanghai, Habitat International, 37: 33-42.
     25.Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In Modern Methods for Business Research, ed. G. A. Marcoulides, 295-336. London: Taylor & Francis.
     26.Chiu, Y.H., and Wu, M. F.(2010). Environmental efficiency evaluation in china: application of `undesirable` data envelopment analysis, Polish Journal of Environmental Studies, 19(6): 1159-1169.
     27.Cooper, W. W., Seiford, L. M., and Tone, K.(2007). Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Boston: Springer-Verlag.
     28.Cooper, W. W., Seiford, L. M., and Zhu, J. (2011). Handbook on Data Envelopment Analysis, Boston: Springer.
     29.Cowan, W. N., Chang, T., Inglesi-Lotz, R., and Gupta, R. (2014). The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries, Energy Policy, 66: 359-368.
     30.Demchuk, P., and Zelenyuk, V. (2009). Testing differences in efficiency of regions within a country: the case of Ukraine, Journal of Productivity Analysis, 32(2): 81-102.
     31.Dodman, D. (2011). Forces driving urban greenhouse gas emissions, Current Opinion in Environmental Sustainability, 3(3): 121-125.
     32.Dorer, V., and Weber, A. (2009). Energy and CO2 emissions performance assessment of residential micro-cogeneration systems with dynamic whole-building simulation programs, Energy Conversion and Management, 50(3): 648-657.
     33.Dunphy, R.T., and Fisher, K. (1996). Transportation, congestion, and density: New insights, Transportation research record: Journal of the Transportation Research Board, 1552: 89-96.
     34.Efron, B. (1979). Bootstrap methods: Another look at the jackknife, Annals of Statistics, 7(1): 1-26.
     35.Esposito Vinzi, V., Chin, W. W., Henseler, J., and Wang, H. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications, Boston: Springer-Verlag.
     36.Ewing, R., Pendall, R., and Chen, D. (2003). Measuring sprawl and its transportation impacts, Transportation research record: Journal of the Transportation Research Board, 1831: 175-183.
     37.Färe, R., Grosskopf, S., and Hernandez-Sancho, F. (2004). Environmental performance: An index number approach, Resource and Energy Economics, 26(4): 343-352.
     38.Färe, R., Grosskopf, S., and Pasurka, C.A. (2001). Accounting for air pollution emissions in measures of state manufacturing productivity growth, Journal of Regional Science, 41(3): 381–409.
     39.Färe, R., Grosskopf, S., Lovell, C. A. K., and Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach, The Review of Economics and Statistics, 71(1): 90-98.
     40.Feliciano, M., and Prosperi, D. C. (2011). Planning for low carbon cities: Reflection on the case of Broward County, Florida, USA, Cities, 28(6): 505-516.
     41.Feng, C., Gao, X., Wu, J., Tang, Y., He, J., Qi, Y., and Zhang,Y. (2014). Greenhouse gas emissions investigation for towns in China: a case study of Xiaolan, Journal of Cleaner Production, 13: 1-10.
     42.Fischer, M.M., and Getis, A. (2010). Handbook of Applied Sapatial Analysis: Software Tools, Methods and Applications, Boston: Springer-Verlag.
     43.Fornell, C., and Larcker, D.F. (1981). Structural equation models with unobservable variables and measurement errors, Journal of Marketing Research, 18(3): 382-388.
     44.Fotheringham, S., and Rogerson, P. (1994). Spatial Analysis and GIS, London: Taylor & Francis.
     45.Frawley, A.M., and Gunderson, R.J. (2009).“Sustainable development indicators: A case study on the city of Flagstaff and Coconino county, International Journal of Sustainable Development and World Ecology, 16(3): 196-204
     46.Giuliano, G., and Narayan, D. (2003). Another look at travel patterns and urban form: The US and Great Britain, Urban studies, 40(11): 2295-2312.
     47.Glaeser, E. L., and Kahn, M. E. (2010). The greenness of cities: Carbon dioxide emissions and urban development, Journal of Urban Economics, 67(3): 404-418.
     48.Gomi, K., Shimada, K., and Matsuoka, Y. (2010). A low-carbon scenario creation method for a local-scale economy and its application in Kyoto city, Energy Policy, 38(9): 4783-4796.
     49.Gossop, C. (2011). Low carbon cities: An introduction to the special issue, Cities, 28(6): 495-497.
     50.Grazi, F., van den Bergh, J.C.J.M., and van Ommeren, J.N. (2008). An empirical analysis of urban form, transport, and global warming, Energy Journal, 29(4): 97-122.
     51.Greene, W. H. (2012). Econometric analysis, Boston: Prentice Hall.
     52.Gu, Z.H., Sun, Q., and Wennersten, R. (2013). Impact of urban residences on energy consumption and carbon emissions: An investigation in Nanjing, China, Sustainable Cities and Society, 7: 52-61.
     53.Gwilliam, K. (2003). Urban transport in developing countries, Transport Reviews, 23(2): 197-216.
     54.Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: Sage.
     55.Hair, J.F., Black, W.C., Babin, B. J., and Anderson, R.E. (2010). Multivariate Data Analysis, New Jersey: Prentice Hall.
     56.Hankey, S., and Marshall, J. D. (2010). Impacts of urban form on future US passenger-vehicle greenhouse gas emissions, Energy Policy, 38(9): 4880-4887.
     57.He, F., Zhang, Q., Lei, J., Fu, W., and Xu, X.(2013). Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs, Energy Policy, 54: 204-213.
     58.HILL, M. (1968).“A goals-achievement matrix for evaluating alternative plans, Journal of the American Institute of Planners, 34(1): 19-28.
     59.Honma, S., and Hu, J. L. (2008). Total-factor energy efficiency of regions in Japan, Energy Policy, 36(2): 821-833.
     60.Honma, S., and Hu, J. L. (2009). Efficient waste and pollution abatements for regions in Japan, International Journal of Sustainable Development and World Ecology, 16(4): 270-285.
     61.Hu, J.L., and Wang, S.C. (2006). Total-Factor Energy Efficiency of Regions in China, Energy Policy, 34(17): 3206-3217.
     62.Hu, J.L., Wang, S.C., and Yeh, F.Y.(2006). Total-factor water efficiency of regions in China, Resources Policy, 31(4): 217-230.
     63.Huang, S. L., Wong, J. H., and Chen, T. C. (1998). A framework of indicator system for measuring Taipei’s urban sustainability, Landscape and Urban Planning, 42: 15-27.
     64.Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies, Strategic Management Journal, 20(2): 195-204.
     65.Ioannis, E. T. (2011). Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA, Resources Policy, 36(2): 159-167.
     66.Ishii, S., Tabushi, S., Aramaki, T., and Hanaki, K. (2010). Impact of future urban form on the potential to reduce greenhouse gas emissions from residential, commercial and public buildings in Utsunomiya, Japan. Energy Policy, 38(9): 4888-4896.
     67.Jo, H.K. (2002). Impacts of urban green space on offsetting carbon emissions for middle Korea, Journal of Environmental Management, 64(2): 115-126.
     68.Kaiser, H. F. (1974). An index of factorial simplicity, Psychometrika, 39: 31-36.
     69.Kasman, A., and Duman, Y. S. (2015). CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: A panel data analysis, Economic Modelling, 44: 97-103.
     70.Kennedy, C., Steinberger, J., Gasson, B., Hansen, Y., Hillman, T., Havranek, M., Pataki, D., Phdungsilp, A., Ramaswami, A., and Mendez, G. V. (2011). Greenhouse gas emissions from global cities, Environmental Science and Technology, 45: 3816-3817.
     71.Kenworthy, J.R. (2003). Transport energy use and greenhouse gases in urban passenger transport systems: A study of 84 global cities, Proceeding of the Third Conference of the Regional Government Network for Sustainable Development, Fremantle: 24-52.
     72.Kharel, G.P., and Charmondusit, K. (2008). Eco-Efficiency Evaluation of Iron Rod Industry in Nepal, Journal of Cleaner Production, 16: 1379-1387.
     73.Kockelman, K.M. (1997). Travel behavior as function of accessibility, land use mixing, and land use balance: evidence from San Francisco Bay Area, Transportation research record: Journal of the Transportation Research Board, 1607: 116-125.
     74.Kumar, S.(2006).Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index, Ecological Economics, 56(2): 280-293.
     75.Lee, C., and Moudon, A.V. (2006). The 3Ds+R: Quantifying land use and urban form correlates of walking, Transportation Research Part D: Transport and Environment, 11(3): 204-215.
     76.Lehtonen, M. (2008). Mainstreaming sustainable development in the OECD through indicators and peer reviews, Sustainable Development, 16(4): 241-250.
     77.Leitão, A.B., Miller, J., Ahern, J., and McGarigal, K. (2006). Measuring Landscapes: A Planner’s Handbook, Washington, D.C.: Island Press.
     78.Li, X.G., Yang, J., and Liu, X.J.(2013). Analysis of Beijing’s environmental efficiency and related factors using a DEA model that considers undesirable outputs, Mathematical and Computer Modelling, 58(5-6): 956-960.
     79.Li, Y., and Li, Y. (2013). Low-carbon City in China. Sustainable Cities and Society, 9: 62-66.
     80.Li,Y., Li,Y., Zhang, H., Liu,Y., Xu, W., and Zhu, X. (2011). Canadian experience in low carbon eco-city development and the implications for China, Energy Procedia, 5: 1791-1795.
     81.Lin, J. J. and Yang, A. T. (2006). Does the compact city paradigm foster sustainability? An empirical study in Taiwan, Environment and Planning B: Planning and Design, 33(3): 365-380.
     82.Lin, J., Jacoby, J., Cui, S., Liu, Y., and Lin, T. (2014). A model for developing a target integrated low carbon city indicator system: The case of Xiamen, China, Ecological Indicators, 40: 51-57.
     83.Lin, J.Y., Cao, B., Cui, S.H., Wang, W., and Bai, X.M. (2010). Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: The case of Xiamen city, China, Energy Policy, 38(9): 5123-5132.
     84.Liu, X., and Sweeney, J. (2012). Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region, Energy Policy, 46: 359-369.
     85.Liu, Z., Dai, Y., Dong, C., and Qi, Y. (2009). Low carbon city: Concepts, international practice and implications for China, Urban Studies, 16(6): 1-7,12.
     86.Livingstone, K. (2007). The mayor’s climate change action plan, London: Greater London Authority.
     87.Long, W. D., Bai, W., Liang, H., Fan, R., and Zhang, G. J. (2010). Urban form and energy vision in low-carbon cities, Building Science, 2: 13-18.
     88.Lopez, R., and Hynes, H. P. (2003). Sprawl in the 1990s: Measurement, distribution, and trends, Urban Affairs Review, 38(3): 325-255.
     89.Lu, C.C., Chiu, Y.H., Shyu, M.K., and Lee, J.H.(2013). Measuring CO2 emission efficiency in OECD countries: Application of the Hybrid Efficiency model, Economic Modelling, 32 :130-135.
     90.MacKinnon, D. P., Krull, J. L., and Lockwood, C. M. (2000). Equivalence of the mediation, confounding, and suppression effect, Prevention Science, 1(4): 173-181.
     91.Marcotullio, P. J., Sarzynski, A., Albrecht, J., and Schulz, N. (2012). The geography of urban greenhouse gas emissions in Asia: A regional analysis, Global Environmental Change, 22(4): 944-958.
     92.McGarigal, K., and Marks, B.J. (1995). FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure, USDA Forest Technique Report, Portland: Pacific Northwest Research Station.
     93.Meng, F.Y., Fan, L.W., Zhou, P., and Zhou, D.Q. (2013).Measuring environmental performance in China’s industrial sectors with non-radial DEA, Mathematical and Computer Modelling, 58(5-6): 1047-1056.
     94.Nader, M.R., Salloum, B.A., and Karam, N. (2007). Environment and sustainable development indicators in Lebanon: A practical municipal level approach, Ecological Indicators, 8(5): 771-777.
     95.Narayan C. G. (2004). Multivariate Statistical Analysis, New York: Marcel Dekker.
     96.Newman, P.W.G. (1999). Sustainability and cities: Extending the metabolism model, Landscape and Urban Planning, 44(4): 219-226.
     97.Olesen, O. B., and Petersen, N. C. (1995). Incorporating quality into data envelopment analysis: A stochastic dominance approach, International Journal of Production Economics, 39(1-2): 117-135.
     98.Pao, H. T., and Tsai, C. M. (2010).CO2 emissions, energy consumption and economic growth in BRIC countries, Energy Policy, 38(12): 7850-7860.
     99.Parshall, L., Gurney, K., Hammer, S. A., Mendoza, D., Zhou, Y., and Geethakumar, S. (2010). Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States, Energy Policy, 38(9): 4765-4782.
     100.Perkins, A., and Hamnett, S. (2005). The significance of urban form in creating more greenhouse-friendly cities, Proceeding of the 8th Asian Planning Schools Conference, Penang, 1-13.
     101.Phdungsilp, A. (2010). Integrated energy and carbon modeling with a decision support system: Policy scenarios for low-carbon city development in Bangkok, Energy Policy, 38(9): 4808-4817.
     102.Poumanyvong, P., and Kaneko,S. (2010). Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis, Ecological Economics, 70(2): 434-444.
     103.Price, L., Zhou, N., Fridley, D., Ohshita, S., Lu, H. Y., Zheng, N. N., and Fino-Chen, C. (2013). Development of a low-carbon indicator system for China, Habitat International, 37: 4-21.
     104.Pucher, J., Peng, Z.R., Mittal, N., Zhu, Y., and Korattyswaroopam, N. (2007). Urban transport trends and policies in China and India: Impacts of rapid economic growth, Transport Reviews, 27(4): 379-410.
     105.Rao, X., Wu, J., Zhang, Z.Y., and Liu, B.(2012). Energy efficiency and energy saving potential in China: An analysis based on slacks-based measure model, Computers & Industrial Engineering, 63(3): 578-584.
     106.Ravetz, J. (2000). City-Region 2020: Integrated planning for a sustainable environment, London: Earthscan publications.
     107.Russo, M. V., and Fouts, P. A. (1997). A resource-based perspective on corporate environmental performance and profitability, The Academy of Management Journal, 40(3): 534-559.
     108.Salahuddin, M., and Gow, J. (2014). Economic growth, energy consumption and CO2 emissions in Gulf Cooperation Council countries, Energy, 73: 44-58.
     109.Seiford, L.M., and Zhu, J.(2002).Modeling undesirable factors in efficiency evaluation, European Journal of Operational Research, 142(1): 16-20.
     110.Shen, Q. (1997). Urban transportation in Shanghai, China: Problems and planning implications, International Journal of Urban and Regional Research, 21(4): 589-606.
     111.Shimada, K., Tanaka, Y., Gomi, K., and Matsuoka, Y. (2007). Developing a long-term local society design methodology towards a low-carbon economy: An application to Shiga Prefecture in Japan, Energy Policy, 35(9): 4688-4703.
     112.Shrout, P. E., and Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations, Psychological Methods, 7(4): 422-445.
     113.Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models, Sociological Methodology, 16: 159-186.
     114.Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor M., and Miller, H.L. (2007). Climate Change 2007: The Physical Science Basis-Working Group I Contribution to IPCC Fourth Assessment Report, New York: Cambridge University Press.
     115.Song, I.J., Hong, S.K., Kim, H.O., Byun, B., and Gin, Y. (2005). The pattern of landscape patches and invasion of naturalized plants in developed areas of urban Seoul, Landscape and Urban Planning, 70(3-4): 205-219.
     116.Song,M., Song,Y., An, Q., and Yu, H.(2013). Review of environmental efficiency and its influencing factors in China: 1998-2009, Renewable and Sustainable Energy Reviews, 20: 8-14.
     117.Su, M. R., Chen, B., Xing, T., Chen, C., and Yang, Z. F. (2012). Development of low-carbon city in China: Where will it go? Procedia Environmental Sciences, 13: 1143-1148.
     118.Tabachnick, B. G., and Fidell, L. S. (2001). Using Multivariate Statistics, Boston: Allyn and Bacon.
     119.Tao, Y. and Zhang, S.(2013). Environmental efficiency of electric power industry in the Yangtze River Delta, Mathematical and Computer Modelling, 58(5-6): 927-935.
     120.Tenenhaus, M., Amato, S., and Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modeling, Proceedings of the XLII SIS scientific meeting, 739-742.
     121.Timm, N. H. (2012). Applied Multivariate Analysis, New York : Springer.
     122.Tone, K. (2003). Dealing with Undesirable Outputs in DEA: A Slacks-Based Measure(SBM)Approach, Tokyo: National Graduate Institute for Policy Studies.
     123.Tone, K.(2001). A slacks-based measure of efficiency in data envelopment analysis, European Journal Of Operational Research, 130(3): 498-509.
     124.Tyteca, D.(1996).On the measurement of the environmental performance of firms: A literature review and a productive efficiency perspective, Journal of Environmental Management, 46(3): 281-308.
     125.Unger, N., Bond, T.C., Wang, J.S., Koch, D.M., Menon, S., Shindell, D.T., and Bauer, S. (2010). Attribution of climate forcing to economic sectors, Proceedings of the National Academy of Sciences, 107(8): 3382-3387.
     126.Vaccari, F. P., Gioli, B., Toscano, P., and Perrone, C. (2013). Carbon dioxide balance assessment of the city of Florence (Italy), and implications for urban planning, Landscape and Urban Planning, 120: 138-146.
     127.Wang, B., and Sun, Y. (2011). Evaluation system and empirical research on the development of low carbon economy-taking Daqing as an example, Energy Procedia, 5: 435-439.
     128.Wang, H.S., Wang, Y.X., Wang, H.K., Liu, M.M., Zhang, Y.X., Zhang, R.R., Yang, J., and Bi, J. (2014). Mitigating greenhouse gas emissions from China`s cities: Case study of Suzhou, Energy Policy, 68: 482-489.
     129.Wang, K., Wei, Y.M., and Zhang, X.(2012). A comparative analysis of China`s regional energy and emission performance: Which is the better way to deal with undesirable outputs, Energy Policy, 46: 574-584.
     130.Wang, S., Fang, C., Guan, X., Pang, B., and Ma, H. (2014). Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces, Applied Energy, 136: 738-749.
     131.Weissert, L.F., Salmond, J.A., and Schwendenmann, L. (2014). A review of the current progress in quantifying the potential of urban forests to mitigate urban CO2 emissions, Urban Climate, 8: 100-125.
     132.Wetzels, M., Odekerken-Schröder, G., and van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration, MIS Quartery, 33(1):177-195.
     133.Wu, F., Fan, L.W., Zhou, P., and Zhou, D.Q.(2012). Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis, Energy Policy, 49: 164-172.
     134.Wu, J., An, Q.X., Xiong, B.B., and Chen, Y.(2013).Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs, Energy Policy, 57 :7-13.
     135.Xu, P.P., Chan, E.H.W., and Qian, Q.K. (2011). Success factors of energy performance contracting (EPC) for sustainable building energy efficiency retrofit (BEER) of hotel buildings in China, Energy Policy, 39(11): 7389-7398.
     136.Yang, J., McBride, J., Zhou, J., and Sun, Z. (2005). The urban forest in Beijing and its role in air pollution reduction, Urban Forestry and Urban Greening, 3(2): 65-78.
     137.Zhang, B., Bi, J., Fan, Z., Yuan, Z., and Ge, J. (2008). Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach, Ecological Economics, 68: 306-316.
     138.Zhang, L.X., Feng, Y.Y., and Chen, B. (2011). Alternative scenarios for the development of a low-carbon city: A case study of Beijing, China, Energies, 4(12): 2295-2310.
     139.Zhang, L.X., Yang, Z.F., Liang, J., and Cai, Y.P. (2011). Spatial variation and distribution of urban energy consumptions from cities in China, Energies, 4(1): 26-38.
     140.Zhang, N., and Choi, Y. (2013). Environmental energy efficiency of China`s regional economies: A non-oriented slacks-based measure analysis, Social Science Journal, 50(2): 225-234.
     141.Zhang,T. (2011). Strategy of city development in low-carbon economic mode—A case study on Qingdao, Energy Procedia, 5: 926-932.
     142.Zhao, P.J., and Lu, B. (2011). Managing urban growth to reduce motorised travel in Beijing: One method of creating a low-carbon city, Journal of Environmental Planning and Management, 54(7): 959-977.
     143.Zhao, P.J., Lue, B., and de Roo, G. (2011). Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era, Journal of transport geography, 19 (1): 59-69.
     144.Zhou, P., Ang, B. W., and Han, J. Y. (2010). Total factor carbon emission performance: A Malmquist index analysis, Energy Economics, 32(1): 194-201.
     145.Zhou, P., Ang, B. W., Poh, K. L.(2006).Slacks-based efficiency measures for modeling environmental performance, Ecological Economics, 60(1): 111-118.
     146.Zhou, P., Poh, K.L., and Ang, B.W.(2007).A non-radial DEA approach to measuring environmental performance, European Journal of Operational Research, 178(1): 1-9.
     147.Zofio, J.L., and Prieto, A.M.(2001).Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries, Resource and Energy Economics, 23(1): 63-83.
     148.丁蕙萱(2012)，建構低碳社區基礎之智慧綠建築，「臺灣經濟研究」，35(8)：55-61。
     149.方精雲、郭兆迪、朴世龍、陳安平(2007)，1981-2000年中國陸地植被碳匯的估算，「中國科學(D輯:地球科學)」，37(6)：804-812。
     150.付允、汪雲林、李丁(2008)，低碳城市的發展路徑研究，「科學對社會的影響」，2008(2)：5-10。
     151.付允、劉怡君、汪雲林(2010)，低碳城市的評價方法與支撐體系研究，「中國人口、資源與環境」，2010(8)：45-47。
     152.田水承、薛明月、李廣利、李磊(2013)，基於因數分析法的礦工不安全行為影響因素權重確定，「礦業安全與環保」，2013(5)：113-116，123。
     153.行政院(2014)，「國家綠能低碳總行動方案103年度工作計畫」，臺北：行政院。
     154.何勇(2006)，「中國氣候、陸地生態系統碳迴圈研究」，北京：氣象出版社。
     155.呂錫民(2013)，我國低碳能源策略分析，「碳經濟」，28：29-52。
     156.李永展、林士堅、黃慶銘(2008)，臺北市永續發展指數之建構及應用，「建築學報」，65：1-26。
     157.李沛濠、黃麟傑、陳庚轅、洪明龍(2014)，我國低碳技術發展及應用－澎湖低碳島，「電機月刊」，24(4)：144-153。
     158.李玲瑜(2012)，日、韓推動低碳綠色城鎮之探討，「臺灣經濟研究」，35(4)：77-83。
     159.李珣琮、謝明叡、陳俞婷(2012)，我國低碳社區及能源智慧社區推動情形及課題，「臺灣經濟研究」，35(8)：39-47。
     160.李堅明(2008)，淺論國際溫室氣體管理發展趨勢，「能源報導」，2008(10)：11-13。
     161.李堅明(2009)，國際推動低碳社會之策略與經驗，「能源報導」，2009(6)：頁5-7。
     162.李堅明(2010)，低碳經濟與節能減碳技術發展策略，「永續產業發展」，49：63-67。
     163.李堅明、曾盟峰(2012)，我國與OECD國家之產業低碳轉型策略與作法比較，「永續產業發展」，58：32-42。
     164.李堅明、廖喜堂、葉鈞喬(2014)，碳捕獲封存技術與國家新能源政策之選擇價值評估，「臺灣能源期刊」，1(3)：349-366。
     165.沈清基、安超、劉昌壽(2012)，「低碳生態城市理論與實踐」，北京：中國城市出版社。
     166.辛玲(2011)，低碳城市評價指標體系的構建，「統計與決策」，2011(7)：78-80。
     167.林沛傑(2009)，低碳供應鏈時代對於物流業的衝擊與機會，「物流技術與戰略」，69：26-28。
     168.林楨家、楊恩捷(2006)，都市型態對旅運需求影響之結構化分析，「運輸學刊」，18(4)：391-416。
     169.林楨家、蕭博正(2006)，臺北市土地混合使用特性對旅次發生之影響，「臺灣土地研究」，9(1)：89-114。
     170.施冠宇、花佳正(2010)，因應全球減碳潮流，審視石化產業發展與我國能源政策，「臺灣經濟研究」，33(10)：39-45。
     171.郎若帆(2009)，構築低碳社會的願景，「臺灣經濟研究」，32(11)：70-77。
     172.夏堃堡(2008)，發展低碳經濟，實現城市可持續發展，「環境保護」，2008(2A)：33-35。
     173.馬公勉(2009)，引領臺灣產業邁向低碳化，「臺灣經濟研究」，32(6)：50-56。
     174.張學聖、郭婷婷、陳姿伶(2014)，從碳平衡觀點探討都市空間發展之特性－以臺灣各縣市為例，「建築學報」，87：137-157。
     175.張憶琳(2009)，低碳家園政策與我國綠色能源產業發展，「永續產業發展」，45：20-25。
     176.章朝榮(2012)，中國低碳城鎮發展趨勢，「臺灣經濟研究」，35(4)：84-88。
     177.許淑麗、林家弘、王珮蓉(2010)，建構企業低碳經營策略路徑之探討－由溫室氣體盤查、產品碳足跡到低碳生產/碳中和，「永續產業發展」，49：55-62。
     178.陳永凍、高淑芳、李龍堯(2010)，推動綠色技術服務業落實節能減碳，「工業污染防治」，29(1)：105-118。
     179.陳星皓(2014)，低碳趨勢下之智慧化健康建築環境促進策略，「健康與建築雜誌」，1(3)：10-14。
     180.陳玲慧(2009)，低碳社會政府與民眾角色之扮演，「永續產業發展」，43：38-47。
     181.陳雅琴(2009)，國內低碳能源使用推廣與因應配套，「臺灣經濟研究」，32(6)：57-65。
     182.陳順宇(2005)，「多變量分析」，臺北：華泰文化事業股份有限公司。
     183.單珮玲(2012)，建構低碳城市--推動永續自償之財政機制，「當代財政」，17：39-49。
     184.彭敏瑜、李沃牆(2011)，臺灣銀行業對低碳經濟之因應發展策略，「臺灣經濟金融」，47(12)：1-13。
     185.黃書禮(1999)，「生態土地使用規劃」，臺北：詹氏書局。
     186.黃書禮、葉佳宗、陳俐伶(2005)，檢視都市永續發展指標的發展歷程與內涵：從指標系統建構到政策評估，「都市與計劃」，32(2)：227-251。
     187.黃釋緯(2008)，節能減碳技術之發展趨勢與推廣策略，「臺灣經濟研究」，31(8)：62-67。
     188.楊惟任(2014)，氣候變遷與政府：低碳轉型的經濟、政治與社會分析，「國會」，42(6)：27-41。
     189.經建會經濟研究處(2013)，擘劃綠色新政，邁向低碳永續－臺灣節能減碳推動計畫與執行成果，「臺灣經濟論衡」，11(3)：20-42。
     190.路正南、孫少美(2011)，城市低碳化可持續發展指標初探，「科技管理研究」，31(4)：57-59。
     191.廖宗聖(2012)，中國減緩氣候變遷的政策與法制：以經濟發展為軸，以能源策略、法制進行回應，「臺灣國際法季刊」，9(1)：49-85。
     192.趙琳、范德成(2011)，我國高技術產業技術創新效率的測度及動態演化分析—基於因數分析定權法的分析，「科技進步與對策」，2011(11)：111-115。
     193.歐嘉瑞(2013)，我國節能減碳執行成效及檢討，「碳經濟」，31：2-20。
     194.練福星、林杰宏、侯雅壹(2014)，低碳社區評估指標及排碳量推估，「健康與建築雜誌」，1(3)：1-9。
     195.鄧振源(2005)，「計畫評估：方法與應用」，基隆：運籌規劃與管理研究中心。
     196.鄭柔佑、陳怡君、朱志弘、許裴鈞、楊博傑、張根穆、傅豫東、陳世偉(2014)，低碳生活圈碳減緩策略評析，「臺灣能源期刊」，1(4)：449-462。
     197.戴亦欣(2009)，中國低碳城市發展的必要性和治理模式分析，「中國人口、資源與環境」，2009(3)：12-17。
     198.顧朝林(2013)，「氣候變化與低碳城市規劃」，南京：東南大學出版社。
描述 博士
國立政治大學
地政研究所
98257501
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0982575011
資料類型 thesis
dc.contributor.advisor 劉小蘭zh_TW
dc.contributor.advisor Liu, Hsiao Lanen_US
dc.contributor.author (Authors) 沈育生zh_TW
dc.contributor.author (Authors) Shen, Yu Shengen_US
dc.creator (作者) 沈育生zh_TW
dc.creator (作者) Shen, Yu Shengen_US
dc.date (日期) 2015en_US
dc.date.accessioned 27-Jul-2015 11:32:25 (UTC+8)-
dc.date.available 27-Jul-2015 11:32:25 (UTC+8)-
dc.date.issued (上傳時間) 27-Jul-2015 11:32:25 (UTC+8)-
dc.identifier (Other Identifiers) G0982575011en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76923-
dc.description (描述) 博士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 地政研究所zh_TW
dc.description (描述) 98257501zh_TW
dc.description.abstract (摘要) 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。		zh_TW
dc.description.abstract (摘要) 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.		en_US
dc.description.tableofcontents 第一章 緒論......................................1-1
     第一節 研究動機與目的...................1-1
     第二節 研究課題及構想...................1-5
     第三節 研究範疇........................1-7
     第四節 研究架構與內容...................1-9
     第五節 研究方法........................1-12
     第六節 研究限制........................1-16
     第二章 理論與文獻評述..............................2-1
     第一節 低碳都市之發展...................2-1
     第二節 低碳都市與其相關研究之探討.........2-5
     第三節 台灣低碳政策及低碳研究之進展.......2-13
     第四節 分析方法之論述及應用..............2-16
     第五節 綜合評述........................2-23
     第三章 低碳都市衡量指標系統之建構及探討...............3-1
     第一節 研究背景之論述...................3-1
     第二節 實證分析設計.....................3-2
     第三節 樣本資料說明.....................3-9
     第四節 低碳都市指標系統之建立.............3-11
     第五節 各縣市低碳發展狀態之衡量...........3-18
     第六節 各縣市低碳發展狀態之群落劃分........3-20
     第七節 小結............................3-22
     第四章 縣市低碳發展效率評估及低碳政策影響效果之探討.....4-1
     第一節 研究背景之論述....................4-1
     第二節 實證分析之設計....................4-3
     第三節 樣本資料說明......................4-12
     第四節 縣市低碳發展效率評估...............4-14
     第五節 低碳政策對縣市低碳發展效率之影響效果..4-17
     第六節 小結.............................4-20
     第五章 都市發展及空間結構與碳量關係之探討.............5-1
     第一節 研究背景之論述.....................5-1
     第二節 實證分析設計.......................5-3
     第三節 樣本資料說明.......................5-10
     第四節 都市發展及空間結構對碳量之影響效果.....5-12
     第五節 小結..............................5-17
     第六章 結論與建議.................................6-1
     第一節 結論..............................6-1
     第二節 建議..............................6-5
     參考文獻..........................................參-1		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0982575011en_US
dc.subject (關鍵詞) 低碳都市zh_TW
dc.subject (關鍵詞) 指標系統zh_TW
dc.subject (關鍵詞) 低碳發展效率zh_TW
dc.subject (關鍵詞) 低碳政策zh_TW
dc.subject (關鍵詞) 空間結構zh_TW
dc.subject (關鍵詞) 碳量zh_TW
dc.subject (關鍵詞) Low-Carbon Cityen_US
dc.subject (關鍵詞) Indicator Systemen_US
dc.subject (關鍵詞) Low-Carbon Efficiencyen_US
dc.subject (關鍵詞) Low-Carbon Policiesen_US
dc.subject (關鍵詞) Spatial Structureen_US
dc.subject (關鍵詞) Carbon Emissionsen_US
dc.title (題名) 低碳都市評估及其空間結構之分析zh_TW
dc.title (題名) Evaluating the Efficiency of Low-Carbon City and Analyzing the Effects of Spatial Structure on Carbon Emissionsen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1.Anderson, W. P., Kanaroglou, P. S., and Miller, E. J. (1996).Urban form, energy and the environment: A review of issues, evidence and policy, Urban Studies, 33:7-35.
     2.Aragon-Correa, J.A. (1998). Strategic proactivity and firm approach to the natural environment, The Academy of Management Journal, 41(5): 556-567.
     3.Arcelus, F., and Arocena, P.(2005). Productivity differences across OECD countries in the presence of environmental constraints, Journal of the Operational Research Society, 56(12): 1352-1362.
     4.Baeumler, A., Ijjasz-Vasquez, E., and Mehndiratta, S. (2012). Sustainable Low-Carbon City Development in China, New York: World Bank Publications.
     5.Barkalow, G., Bemis, G., McKeever, N., Phinney, S., and Vinton, J. (2007). The Role of Land Use in Meeting California’s Energy and Climate Change Goals, California: California Energy Commission.
     6.Barney, J. B. (1991). Firm resources and sustained competitive advantage, Journal of Management, 17(1): 99-120.
     7.Barter, P.A. (2000). Transport dilemmas in dense urban areas: examples from Eastern Asia. In Compact cities: Sustainable urban forms for developing countries, ed. M. Jenks, and R. Burgess, 271-284. London: E & FN Spon.
     8.Basiago, A. D. (1998). Economic, social, and environmental sustainability in development theory and urban planning practice, Environmentalist, 19(2): 145-161.
     9.Beatley, T. (2000). Green Urbanism: Learning from European Cities, Washington, D.C.: Island Press.
     10.Bella, G., Massidda, C., and Mattana, P. (2014). The relationship among CO2 emissions, electricity power consumption and GDP in OECD countries, Journal of Policy Modeling, 36(6): 970-985.
     11.Bi, J., Zhang, R.R., Wang, H.K., Liu, M.M., and Wu, Y. (2011). The benchmarks of carbon emissions and policy implications for China`s cities: Case of Nanjing, Energy Policy, 39(9): 4785-4794.
     12.Bollen, K. A. (1989). Structural equations with Latent Variables. New York: Wiley.
     13.Boussofiane, A., Dyson, R. G., and Thanassoulis, E. (1991). Applied Data Envelopment Analysis, European Journal of Operational Research, 52: 1-15.
     14.Burton, E. (2002). Measuring urban compactness in UK towns and cities, Environment and Planning B: Planning and Design, 29: 219-250.
     15.Cai, B.F., Wang, J.N., Yang, W.S., Liu, L.C., and Cao, D. (2012). Low carbon society in China: Research and practice, Advances in Climate Change Research, 3(2): 106-120.
     16.Cervero, R. (1996). Mixed land-uses and commuting: Evidence from the American housing survey, Transportation Research Part A: Policy And Practice, 30(5): 361-377.
     17.Cervero, R., and Day, J. (2008).Suburbanization and transit-oriented development in China, Transport Policy, 15(5): 315-323.
     18.Cervero, R., and Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design, Transportation Research Part D: Transport and Environment, 2(3): 99-219.
     19.Chan, H.W., Choy, H.T., and Yung, H.K. (2013). Current research on low-carbon cities and institutional responses, Habitat International, 37: 1-3.
     20.Chang, Y.T., Zhang, N., Danao, D., and Zhang, N.(2013). Environmental efficiency analysis of transportation system in China: A non-radial DEA approach, Energy Policy, 58: 277-283.
     21.Chapman, R. (2008).Transitioning to low-carbon urban form and transport in New Zealand, Political Science, 60(1): 89-98.
     22.Charmondusit, K. And Keartpakpraek K. (2010). Eco-Efficiency Evaluation of the Petroleum and Petrochemical Group in the Map Ta Phut Industrial Estate, Tailand, Journal of Cleaner Production, 19(2-3): 241–252.
     23.Chatham House, Chinese Academy of Social Sciences, Energy Research Institute, Jilin University, E3G. (2010). Low Carbon Development Roadmap for Jilin City, London: Royal Institute of International Affairs.
     24.Chen, F., and Zhu, D. (2013). Theoretical research on low-carbon city and empirical study of Shanghai, Habitat International, 37: 33-42.
     25.Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In Modern Methods for Business Research, ed. G. A. Marcoulides, 295-336. London: Taylor & Francis.
     26.Chiu, Y.H., and Wu, M. F.(2010). Environmental efficiency evaluation in china: application of `undesirable` data envelopment analysis, Polish Journal of Environmental Studies, 19(6): 1159-1169.
     27.Cooper, W. W., Seiford, L. M., and Tone, K.(2007). Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Boston: Springer-Verlag.
     28.Cooper, W. W., Seiford, L. M., and Zhu, J. (2011). Handbook on Data Envelopment Analysis, Boston: Springer.
     29.Cowan, W. N., Chang, T., Inglesi-Lotz, R., and Gupta, R. (2014). The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries, Energy Policy, 66: 359-368.
     30.Demchuk, P., and Zelenyuk, V. (2009). Testing differences in efficiency of regions within a country: the case of Ukraine, Journal of Productivity Analysis, 32(2): 81-102.
     31.Dodman, D. (2011). Forces driving urban greenhouse gas emissions, Current Opinion in Environmental Sustainability, 3(3): 121-125.
     32.Dorer, V., and Weber, A. (2009). Energy and CO2 emissions performance assessment of residential micro-cogeneration systems with dynamic whole-building simulation programs, Energy Conversion and Management, 50(3): 648-657.
     33.Dunphy, R.T., and Fisher, K. (1996). Transportation, congestion, and density: New insights, Transportation research record: Journal of the Transportation Research Board, 1552: 89-96.
     34.Efron, B. (1979). Bootstrap methods: Another look at the jackknife, Annals of Statistics, 7(1): 1-26.
     35.Esposito Vinzi, V., Chin, W. W., Henseler, J., and Wang, H. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications, Boston: Springer-Verlag.
     36.Ewing, R., Pendall, R., and Chen, D. (2003). Measuring sprawl and its transportation impacts, Transportation research record: Journal of the Transportation Research Board, 1831: 175-183.
     37.Färe, R., Grosskopf, S., and Hernandez-Sancho, F. (2004). Environmental performance: An index number approach, Resource and Energy Economics, 26(4): 343-352.
     38.Färe, R., Grosskopf, S., and Pasurka, C.A. (2001). Accounting for air pollution emissions in measures of state manufacturing productivity growth, Journal of Regional Science, 41(3): 381–409.
     39.Färe, R., Grosskopf, S., Lovell, C. A. K., and Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach, The Review of Economics and Statistics, 71(1): 90-98.
     40.Feliciano, M., and Prosperi, D. C. (2011). Planning for low carbon cities: Reflection on the case of Broward County, Florida, USA, Cities, 28(6): 505-516.
     41.Feng, C., Gao, X., Wu, J., Tang, Y., He, J., Qi, Y., and Zhang,Y. (2014). Greenhouse gas emissions investigation for towns in China: a case study of Xiaolan, Journal of Cleaner Production, 13: 1-10.
     42.Fischer, M.M., and Getis, A. (2010). Handbook of Applied Sapatial Analysis: Software Tools, Methods and Applications, Boston: Springer-Verlag.
     43.Fornell, C., and Larcker, D.F. (1981). Structural equation models with unobservable variables and measurement errors, Journal of Marketing Research, 18(3): 382-388.
     44.Fotheringham, S., and Rogerson, P. (1994). Spatial Analysis and GIS, London: Taylor & Francis.
     45.Frawley, A.M., and Gunderson, R.J. (2009).“Sustainable development indicators: A case study on the city of Flagstaff and Coconino county, International Journal of Sustainable Development and World Ecology, 16(3): 196-204
     46.Giuliano, G., and Narayan, D. (2003). Another look at travel patterns and urban form: The US and Great Britain, Urban studies, 40(11): 2295-2312.
     47.Glaeser, E. L., and Kahn, M. E. (2010). The greenness of cities: Carbon dioxide emissions and urban development, Journal of Urban Economics, 67(3): 404-418.
     48.Gomi, K., Shimada, K., and Matsuoka, Y. (2010). A low-carbon scenario creation method for a local-scale economy and its application in Kyoto city, Energy Policy, 38(9): 4783-4796.
     49.Gossop, C. (2011). Low carbon cities: An introduction to the special issue, Cities, 28(6): 495-497.
     50.Grazi, F., van den Bergh, J.C.J.M., and van Ommeren, J.N. (2008). An empirical analysis of urban form, transport, and global warming, Energy Journal, 29(4): 97-122.
     51.Greene, W. H. (2012). Econometric analysis, Boston: Prentice Hall.
     52.Gu, Z.H., Sun, Q., and Wennersten, R. (2013). Impact of urban residences on energy consumption and carbon emissions: An investigation in Nanjing, China, Sustainable Cities and Society, 7: 52-61.
     53.Gwilliam, K. (2003). Urban transport in developing countries, Transport Reviews, 23(2): 197-216.
     54.Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: Sage.
     55.Hair, J.F., Black, W.C., Babin, B. J., and Anderson, R.E. (2010). Multivariate Data Analysis, New Jersey: Prentice Hall.
     56.Hankey, S., and Marshall, J. D. (2010). Impacts of urban form on future US passenger-vehicle greenhouse gas emissions, Energy Policy, 38(9): 4880-4887.
     57.He, F., Zhang, Q., Lei, J., Fu, W., and Xu, X.(2013). Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs, Energy Policy, 54: 204-213.
     58.HILL, M. (1968).“A goals-achievement matrix for evaluating alternative plans, Journal of the American Institute of Planners, 34(1): 19-28.
     59.Honma, S., and Hu, J. L. (2008). Total-factor energy efficiency of regions in Japan, Energy Policy, 36(2): 821-833.
     60.Honma, S., and Hu, J. L. (2009). Efficient waste and pollution abatements for regions in Japan, International Journal of Sustainable Development and World Ecology, 16(4): 270-285.
     61.Hu, J.L., and Wang, S.C. (2006). Total-Factor Energy Efficiency of Regions in China, Energy Policy, 34(17): 3206-3217.
     62.Hu, J.L., Wang, S.C., and Yeh, F.Y.(2006). Total-factor water efficiency of regions in China, Resources Policy, 31(4): 217-230.
     63.Huang, S. L., Wong, J. H., and Chen, T. C. (1998). A framework of indicator system for measuring Taipei’s urban sustainability, Landscape and Urban Planning, 42: 15-27.
     64.Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies, Strategic Management Journal, 20(2): 195-204.
     65.Ioannis, E. T. (2011). Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA, Resources Policy, 36(2): 159-167.
     66.Ishii, S., Tabushi, S., Aramaki, T., and Hanaki, K. (2010). Impact of future urban form on the potential to reduce greenhouse gas emissions from residential, commercial and public buildings in Utsunomiya, Japan. Energy Policy, 38(9): 4888-4896.
     67.Jo, H.K. (2002). Impacts of urban green space on offsetting carbon emissions for middle Korea, Journal of Environmental Management, 64(2): 115-126.
     68.Kaiser, H. F. (1974). An index of factorial simplicity, Psychometrika, 39: 31-36.
     69.Kasman, A., and Duman, Y. S. (2015). CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: A panel data analysis, Economic Modelling, 44: 97-103.
     70.Kennedy, C., Steinberger, J., Gasson, B., Hansen, Y., Hillman, T., Havranek, M., Pataki, D., Phdungsilp, A., Ramaswami, A., and Mendez, G. V. (2011). Greenhouse gas emissions from global cities, Environmental Science and Technology, 45: 3816-3817.
     71.Kenworthy, J.R. (2003). Transport energy use and greenhouse gases in urban passenger transport systems: A study of 84 global cities, Proceeding of the Third Conference of the Regional Government Network for Sustainable Development, Fremantle: 24-52.
     72.Kharel, G.P., and Charmondusit, K. (2008). Eco-Efficiency Evaluation of Iron Rod Industry in Nepal, Journal of Cleaner Production, 16: 1379-1387.
     73.Kockelman, K.M. (1997). Travel behavior as function of accessibility, land use mixing, and land use balance: evidence from San Francisco Bay Area, Transportation research record: Journal of the Transportation Research Board, 1607: 116-125.
     74.Kumar, S.(2006).Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index, Ecological Economics, 56(2): 280-293.
     75.Lee, C., and Moudon, A.V. (2006). The 3Ds+R: Quantifying land use and urban form correlates of walking, Transportation Research Part D: Transport and Environment, 11(3): 204-215.
     76.Lehtonen, M. (2008). Mainstreaming sustainable development in the OECD through indicators and peer reviews, Sustainable Development, 16(4): 241-250.
     77.Leitão, A.B., Miller, J., Ahern, J., and McGarigal, K. (2006). Measuring Landscapes: A Planner’s Handbook, Washington, D.C.: Island Press.
     78.Li, X.G., Yang, J., and Liu, X.J.(2013). Analysis of Beijing’s environmental efficiency and related factors using a DEA model that considers undesirable outputs, Mathematical and Computer Modelling, 58(5-6): 956-960.
     79.Li, Y., and Li, Y. (2013). Low-carbon City in China. Sustainable Cities and Society, 9: 62-66.
     80.Li,Y., Li,Y., Zhang, H., Liu,Y., Xu, W., and Zhu, X. (2011). Canadian experience in low carbon eco-city development and the implications for China, Energy Procedia, 5: 1791-1795.
     81.Lin, J. J. and Yang, A. T. (2006). Does the compact city paradigm foster sustainability? An empirical study in Taiwan, Environment and Planning B: Planning and Design, 33(3): 365-380.
     82.Lin, J., Jacoby, J., Cui, S., Liu, Y., and Lin, T. (2014). A model for developing a target integrated low carbon city indicator system: The case of Xiamen, China, Ecological Indicators, 40: 51-57.
     83.Lin, J.Y., Cao, B., Cui, S.H., Wang, W., and Bai, X.M. (2010). Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: The case of Xiamen city, China, Energy Policy, 38(9): 5123-5132.
     84.Liu, X., and Sweeney, J. (2012). Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region, Energy Policy, 46: 359-369.
     85.Liu, Z., Dai, Y., Dong, C., and Qi, Y. (2009). Low carbon city: Concepts, international practice and implications for China, Urban Studies, 16(6): 1-7,12.
     86.Livingstone, K. (2007). The mayor’s climate change action plan, London: Greater London Authority.
     87.Long, W. D., Bai, W., Liang, H., Fan, R., and Zhang, G. J. (2010). Urban form and energy vision in low-carbon cities, Building Science, 2: 13-18.
     88.Lopez, R., and Hynes, H. P. (2003). Sprawl in the 1990s: Measurement, distribution, and trends, Urban Affairs Review, 38(3): 325-255.
     89.Lu, C.C., Chiu, Y.H., Shyu, M.K., and Lee, J.H.(2013). Measuring CO2 emission efficiency in OECD countries: Application of the Hybrid Efficiency model, Economic Modelling, 32 :130-135.
     90.MacKinnon, D. P., Krull, J. L., and Lockwood, C. M. (2000). Equivalence of the mediation, confounding, and suppression effect, Prevention Science, 1(4): 173-181.
     91.Marcotullio, P. J., Sarzynski, A., Albrecht, J., and Schulz, N. (2012). The geography of urban greenhouse gas emissions in Asia: A regional analysis, Global Environmental Change, 22(4): 944-958.
     92.McGarigal, K., and Marks, B.J. (1995). FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure, USDA Forest Technique Report, Portland: Pacific Northwest Research Station.
     93.Meng, F.Y., Fan, L.W., Zhou, P., and Zhou, D.Q. (2013).Measuring environmental performance in China’s industrial sectors with non-radial DEA, Mathematical and Computer Modelling, 58(5-6): 1047-1056.
     94.Nader, M.R., Salloum, B.A., and Karam, N. (2007). Environment and sustainable development indicators in Lebanon: A practical municipal level approach, Ecological Indicators, 8(5): 771-777.
     95.Narayan C. G. (2004). Multivariate Statistical Analysis, New York: Marcel Dekker.
     96.Newman, P.W.G. (1999). Sustainability and cities: Extending the metabolism model, Landscape and Urban Planning, 44(4): 219-226.
     97.Olesen, O. B., and Petersen, N. C. (1995). Incorporating quality into data envelopment analysis: A stochastic dominance approach, International Journal of Production Economics, 39(1-2): 117-135.
     98.Pao, H. T., and Tsai, C. M. (2010).CO2 emissions, energy consumption and economic growth in BRIC countries, Energy Policy, 38(12): 7850-7860.
     99.Parshall, L., Gurney, K., Hammer, S. A., Mendoza, D., Zhou, Y., and Geethakumar, S. (2010). Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States, Energy Policy, 38(9): 4765-4782.
     100.Perkins, A., and Hamnett, S. (2005). The significance of urban form in creating more greenhouse-friendly cities, Proceeding of the 8th Asian Planning Schools Conference, Penang, 1-13.
     101.Phdungsilp, A. (2010). Integrated energy and carbon modeling with a decision support system: Policy scenarios for low-carbon city development in Bangkok, Energy Policy, 38(9): 4808-4817.
     102.Poumanyvong, P., and Kaneko,S. (2010). Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis, Ecological Economics, 70(2): 434-444.
     103.Price, L., Zhou, N., Fridley, D., Ohshita, S., Lu, H. Y., Zheng, N. N., and Fino-Chen, C. (2013). Development of a low-carbon indicator system for China, Habitat International, 37: 4-21.
     104.Pucher, J., Peng, Z.R., Mittal, N., Zhu, Y., and Korattyswaroopam, N. (2007). Urban transport trends and policies in China and India: Impacts of rapid economic growth, Transport Reviews, 27(4): 379-410.
     105.Rao, X., Wu, J., Zhang, Z.Y., and Liu, B.(2012). Energy efficiency and energy saving potential in China: An analysis based on slacks-based measure model, Computers & Industrial Engineering, 63(3): 578-584.
     106.Ravetz, J. (2000). City-Region 2020: Integrated planning for a sustainable environment, London: Earthscan publications.
     107.Russo, M. V., and Fouts, P. A. (1997). A resource-based perspective on corporate environmental performance and profitability, The Academy of Management Journal, 40(3): 534-559.
     108.Salahuddin, M., and Gow, J. (2014). Economic growth, energy consumption and CO2 emissions in Gulf Cooperation Council countries, Energy, 73: 44-58.
     109.Seiford, L.M., and Zhu, J.(2002).Modeling undesirable factors in efficiency evaluation, European Journal of Operational Research, 142(1): 16-20.
     110.Shen, Q. (1997). Urban transportation in Shanghai, China: Problems and planning implications, International Journal of Urban and Regional Research, 21(4): 589-606.
     111.Shimada, K., Tanaka, Y., Gomi, K., and Matsuoka, Y. (2007). Developing a long-term local society design methodology towards a low-carbon economy: An application to Shiga Prefecture in Japan, Energy Policy, 35(9): 4688-4703.
     112.Shrout, P. E., and Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations, Psychological Methods, 7(4): 422-445.
     113.Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models, Sociological Methodology, 16: 159-186.
     114.Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor M., and Miller, H.L. (2007). Climate Change 2007: The Physical Science Basis-Working Group I Contribution to IPCC Fourth Assessment Report, New York: Cambridge University Press.
     115.Song, I.J., Hong, S.K., Kim, H.O., Byun, B., and Gin, Y. (2005). The pattern of landscape patches and invasion of naturalized plants in developed areas of urban Seoul, Landscape and Urban Planning, 70(3-4): 205-219.
     116.Song,M., Song,Y., An, Q., and Yu, H.(2013). Review of environmental efficiency and its influencing factors in China: 1998-2009, Renewable and Sustainable Energy Reviews, 20: 8-14.
     117.Su, M. R., Chen, B., Xing, T., Chen, C., and Yang, Z. F. (2012). Development of low-carbon city in China: Where will it go? Procedia Environmental Sciences, 13: 1143-1148.
     118.Tabachnick, B. G., and Fidell, L. S. (2001). Using Multivariate Statistics, Boston: Allyn and Bacon.
     119.Tao, Y. and Zhang, S.(2013). Environmental efficiency of electric power industry in the Yangtze River Delta, Mathematical and Computer Modelling, 58(5-6): 927-935.
     120.Tenenhaus, M., Amato, S., and Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modeling, Proceedings of the XLII SIS scientific meeting, 739-742.
     121.Timm, N. H. (2012). Applied Multivariate Analysis, New York : Springer.
     122.Tone, K. (2003). Dealing with Undesirable Outputs in DEA: A Slacks-Based Measure(SBM)Approach, Tokyo: National Graduate Institute for Policy Studies.
     123.Tone, K.(2001). A slacks-based measure of efficiency in data envelopment analysis, European Journal Of Operational Research, 130(3): 498-509.
     124.Tyteca, D.(1996).On the measurement of the environmental performance of firms: A literature review and a productive efficiency perspective, Journal of Environmental Management, 46(3): 281-308.
     125.Unger, N., Bond, T.C., Wang, J.S., Koch, D.M., Menon, S., Shindell, D.T., and Bauer, S. (2010). Attribution of climate forcing to economic sectors, Proceedings of the National Academy of Sciences, 107(8): 3382-3387.
     126.Vaccari, F. P., Gioli, B., Toscano, P., and Perrone, C. (2013). Carbon dioxide balance assessment of the city of Florence (Italy), and implications for urban planning, Landscape and Urban Planning, 120: 138-146.
     127.Wang, B., and Sun, Y. (2011). Evaluation system and empirical research on the development of low carbon economy-taking Daqing as an example, Energy Procedia, 5: 435-439.
     128.Wang, H.S., Wang, Y.X., Wang, H.K., Liu, M.M., Zhang, Y.X., Zhang, R.R., Yang, J., and Bi, J. (2014). Mitigating greenhouse gas emissions from China`s cities: Case study of Suzhou, Energy Policy, 68: 482-489.
     129.Wang, K., Wei, Y.M., and Zhang, X.(2012). A comparative analysis of China`s regional energy and emission performance: Which is the better way to deal with undesirable outputs, Energy Policy, 46: 574-584.
     130.Wang, S., Fang, C., Guan, X., Pang, B., and Ma, H. (2014). Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces, Applied Energy, 136: 738-749.
     131.Weissert, L.F., Salmond, J.A., and Schwendenmann, L. (2014). A review of the current progress in quantifying the potential of urban forests to mitigate urban CO2 emissions, Urban Climate, 8: 100-125.
     132.Wetzels, M., Odekerken-Schröder, G., and van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration, MIS Quartery, 33(1):177-195.
     133.Wu, F., Fan, L.W., Zhou, P., and Zhou, D.Q.(2012). Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis, Energy Policy, 49: 164-172.
     134.Wu, J., An, Q.X., Xiong, B.B., and Chen, Y.(2013).Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs, Energy Policy, 57 :7-13.
     135.Xu, P.P., Chan, E.H.W., and Qian, Q.K. (2011). Success factors of energy performance contracting (EPC) for sustainable building energy efficiency retrofit (BEER) of hotel buildings in China, Energy Policy, 39(11): 7389-7398.
     136.Yang, J., McBride, J., Zhou, J., and Sun, Z. (2005). The urban forest in Beijing and its role in air pollution reduction, Urban Forestry and Urban Greening, 3(2): 65-78.
     137.Zhang, B., Bi, J., Fan, Z., Yuan, Z., and Ge, J. (2008). Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach, Ecological Economics, 68: 306-316.
     138.Zhang, L.X., Feng, Y.Y., and Chen, B. (2011). Alternative scenarios for the development of a low-carbon city: A case study of Beijing, China, Energies, 4(12): 2295-2310.
     139.Zhang, L.X., Yang, Z.F., Liang, J., and Cai, Y.P. (2011). Spatial variation and distribution of urban energy consumptions from cities in China, Energies, 4(1): 26-38.
     140.Zhang, N., and Choi, Y. (2013). Environmental energy efficiency of China`s regional economies: A non-oriented slacks-based measure analysis, Social Science Journal, 50(2): 225-234.
     141.Zhang,T. (2011). Strategy of city development in low-carbon economic mode—A case study on Qingdao, Energy Procedia, 5: 926-932.
     142.Zhao, P.J., and Lu, B. (2011). Managing urban growth to reduce motorised travel in Beijing: One method of creating a low-carbon city, Journal of Environmental Planning and Management, 54(7): 959-977.
     143.Zhao, P.J., Lue, B., and de Roo, G. (2011). Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era, Journal of transport geography, 19 (1): 59-69.
     144.Zhou, P., Ang, B. W., and Han, J. Y. (2010). Total factor carbon emission performance: A Malmquist index analysis, Energy Economics, 32(1): 194-201.
     145.Zhou, P., Ang, B. W., Poh, K. L.(2006).Slacks-based efficiency measures for modeling environmental performance, Ecological Economics, 60(1): 111-118.
     146.Zhou, P., Poh, K.L., and Ang, B.W.(2007).A non-radial DEA approach to measuring environmental performance, European Journal of Operational Research, 178(1): 1-9.
     147.Zofio, J.L., and Prieto, A.M.(2001).Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries, Resource and Energy Economics, 23(1): 63-83.
     148.丁蕙萱(2012)，建構低碳社區基礎之智慧綠建築，「臺灣經濟研究」，35(8)：55-61。
     149.方精雲、郭兆迪、朴世龍、陳安平(2007)，1981-2000年中國陸地植被碳匯的估算，「中國科學(D輯:地球科學)」，37(6)：804-812。
     150.付允、汪雲林、李丁(2008)，低碳城市的發展路徑研究，「科學對社會的影響」，2008(2)：5-10。
     151.付允、劉怡君、汪雲林(2010)，低碳城市的評價方法與支撐體系研究，「中國人口、資源與環境」，2010(8)：45-47。
     152.田水承、薛明月、李廣利、李磊(2013)，基於因數分析法的礦工不安全行為影響因素權重確定，「礦業安全與環保」，2013(5)：113-116，123。
     153.行政院(2014)，「國家綠能低碳總行動方案103年度工作計畫」，臺北：行政院。
     154.何勇(2006)，「中國氣候、陸地生態系統碳迴圈研究」，北京：氣象出版社。
     155.呂錫民(2013)，我國低碳能源策略分析，「碳經濟」，28：29-52。
     156.李永展、林士堅、黃慶銘(2008)，臺北市永續發展指數之建構及應用，「建築學報」，65：1-26。
     157.李沛濠、黃麟傑、陳庚轅、洪明龍(2014)，我國低碳技術發展及應用－澎湖低碳島，「電機月刊」，24(4)：144-153。
     158.李玲瑜(2012)，日、韓推動低碳綠色城鎮之探討，「臺灣經濟研究」，35(4)：77-83。
     159.李珣琮、謝明叡、陳俞婷(2012)，我國低碳社區及能源智慧社區推動情形及課題，「臺灣經濟研究」，35(8)：39-47。
     160.李堅明(2008)，淺論國際溫室氣體管理發展趨勢，「能源報導」，2008(10)：11-13。
     161.李堅明(2009)，國際推動低碳社會之策略與經驗，「能源報導」，2009(6)：頁5-7。
     162.李堅明(2010)，低碳經濟與節能減碳技術發展策略，「永續產業發展」，49：63-67。
     163.李堅明、曾盟峰(2012)，我國與OECD國家之產業低碳轉型策略與作法比較，「永續產業發展」，58：32-42。
     164.李堅明、廖喜堂、葉鈞喬(2014)，碳捕獲封存技術與國家新能源政策之選擇價值評估，「臺灣能源期刊」，1(3)：349-366。
     165.沈清基、安超、劉昌壽(2012)，「低碳生態城市理論與實踐」，北京：中國城市出版社。
     166.辛玲(2011)，低碳城市評價指標體系的構建，「統計與決策」，2011(7)：78-80。
     167.林沛傑(2009)，低碳供應鏈時代對於物流業的衝擊與機會，「物流技術與戰略」，69：26-28。
     168.林楨家、楊恩捷(2006)，都市型態對旅運需求影響之結構化分析，「運輸學刊」，18(4)：391-416。
     169.林楨家、蕭博正(2006)，臺北市土地混合使用特性對旅次發生之影響，「臺灣土地研究」，9(1)：89-114。
     170.施冠宇、花佳正(2010)，因應全球減碳潮流，審視石化產業發展與我國能源政策，「臺灣經濟研究」，33(10)：39-45。
     171.郎若帆(2009)，構築低碳社會的願景，「臺灣經濟研究」，32(11)：70-77。
     172.夏堃堡(2008)，發展低碳經濟，實現城市可持續發展，「環境保護」，2008(2A)：33-35。
     173.馬公勉(2009)，引領臺灣產業邁向低碳化，「臺灣經濟研究」，32(6)：50-56。
     174.張學聖、郭婷婷、陳姿伶(2014)，從碳平衡觀點探討都市空間發展之特性－以臺灣各縣市為例，「建築學報」，87：137-157。
     175.張憶琳(2009)，低碳家園政策與我國綠色能源產業發展，「永續產業發展」，45：20-25。
     176.章朝榮(2012)，中國低碳城鎮發展趨勢，「臺灣經濟研究」，35(4)：84-88。
     177.許淑麗、林家弘、王珮蓉(2010)，建構企業低碳經營策略路徑之探討－由溫室氣體盤查、產品碳足跡到低碳生產/碳中和，「永續產業發展」，49：55-62。
     178.陳永凍、高淑芳、李龍堯(2010)，推動綠色技術服務業落實節能減碳，「工業污染防治」，29(1)：105-118。
     179.陳星皓(2014)，低碳趨勢下之智慧化健康建築環境促進策略，「健康與建築雜誌」，1(3)：10-14。
     180.陳玲慧(2009)，低碳社會政府與民眾角色之扮演，「永續產業發展」，43：38-47。
     181.陳雅琴(2009)，國內低碳能源使用推廣與因應配套，「臺灣經濟研究」，32(6)：57-65。
     182.陳順宇(2005)，「多變量分析」，臺北：華泰文化事業股份有限公司。
     183.單珮玲(2012)，建構低碳城市--推動永續自償之財政機制，「當代財政」，17：39-49。
     184.彭敏瑜、李沃牆(2011)，臺灣銀行業對低碳經濟之因應發展策略，「臺灣經濟金融」，47(12)：1-13。
     185.黃書禮(1999)，「生態土地使用規劃」，臺北：詹氏書局。
     186.黃書禮、葉佳宗、陳俐伶(2005)，檢視都市永續發展指標的發展歷程與內涵：從指標系統建構到政策評估，「都市與計劃」，32(2)：227-251。
     187.黃釋緯(2008)，節能減碳技術之發展趨勢與推廣策略，「臺灣經濟研究」，31(8)：62-67。
     188.楊惟任(2014)，氣候變遷與政府：低碳轉型的經濟、政治與社會分析，「國會」，42(6)：27-41。
     189.經建會經濟研究處(2013)，擘劃綠色新政，邁向低碳永續－臺灣節能減碳推動計畫與執行成果，「臺灣經濟論衡」，11(3)：20-42。
     190.路正南、孫少美(2011)，城市低碳化可持續發展指標初探，「科技管理研究」，31(4)：57-59。
     191.廖宗聖(2012)，中國減緩氣候變遷的政策與法制：以經濟發展為軸，以能源策略、法制進行回應，「臺灣國際法季刊」，9(1)：49-85。
     192.趙琳、范德成(2011)，我國高技術產業技術創新效率的測度及動態演化分析—基於因數分析定權法的分析，「科技進步與對策」，2011(11)：111-115。
     193.歐嘉瑞(2013)，我國節能減碳執行成效及檢討，「碳經濟」，31：2-20。
     194.練福星、林杰宏、侯雅壹(2014)，低碳社區評估指標及排碳量推估，「健康與建築雜誌」，1(3)：1-9。
     195.鄧振源(2005)，「計畫評估：方法與應用」，基隆：運籌規劃與管理研究中心。
     196.鄭柔佑、陳怡君、朱志弘、許裴鈞、楊博傑、張根穆、傅豫東、陳世偉(2014)，低碳生活圈碳減緩策略評析，「臺灣能源期刊」，1(4)：449-462。
     197.戴亦欣(2009)，中國低碳城市發展的必要性和治理模式分析，「中國人口、資源與環境」，2009(3)：12-17。
     198.顧朝林(2013)，「氣候變化與低碳城市規劃」，南京：東南大學出版社。		zh_TW