Comparing High and Low Residential Density: Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions

Comparing High and Low Residential Density: Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions
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DOI:
10.1061/(asce)0733-9488(2006)132:1(10
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发表时间:
2006-03
期刊:
Journal of Urban Planning and Development-asce
影响因子:
--
通讯作者:
J. Norman;H. MacLean;C. Kennedy
J. Norman;H. MacLean;C. Kennedy
中科院分区:
其他
文献类型:
--
作者:
J. Norman;H. MacLean;C. Kennedy

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这项研究提供了一个经验评估的能源使用和温室气体GHG排放与高,低住宅开发。城市发展的三大要素被认为是:基础设施的建筑材料,包括住宅、公用事业和道路、建筑运营以及交通、私人汽车和公共交通。从多伦多市的两个案例研究进行了分析。经济投入产出生命周期评估EIO-LCA模型被应用于估计与基础设施建筑材料制造相关的能源使用和温室气体排放。住房和交通的业务需求是使用国家和/或区域平均数据估算的。研究结果表明,在城市发展背景下,减少温室气体排放的最有针对性的措施应针对交通排放,而减少能源使用的最有针对性的措施应侧重于建筑运营。研究结果还表明,低密度郊区开发的能源和温室气体密集度比高密度城市核心开发的人均能源和温室气体密集度高2.0-2.5倍。当功能单元改为单位居住空间时,系数降低到1.0-1.5,说明功能单元的选择与充分理解城市密度效应高度相关。
This study provides an empirical assessment of energy use and greenhouse gas GHG emissions associated with high and low residential development. Three major elements of urban development are considered: construction materials for infrastructure including residential dwellings, utilities, and roads, building operations, and transportation private automobiles and public transit. Two case studies from the City of Toronto are analyzed. An economic input-output life-cycle assessment EIO-LCA model is applied to estimate the energy use and GHG emissions associated with the manufacture of construction materials for infrastructure. Operational requirements for dwellings and transportation are estimated using nationally and/or regionally averaged data. The results indicate that the most targeted measures to reduce GHG emissions in an urban development context should be aimed at transportation emissions, while the most targeted measures to reduce energy usage should focus on building operations. The results also show that low-density suburban development is more energy and GHG intensive by a factor of 2.0-2.5 than high-density urban core development on a per capita basis. When the functional unit is changed to a per unit of living space basis the factor decreases to 1.0-1.5, illustrating that the choice of functional unit is highly relevant to a full understanding of urban density effects.