Explaining Spatial Variations in Residential Energy Usage Intensity in Chicago: The Role of Urban Form and Geomorphometry

被引：25
作者：
Li, Chaosu [1 ,5 ]
Song, Yan [2 ,3 ]
Kaza, Nikhil [3 ]
Burghardt, Rene [4 ]
机构：
[1] City Univ Macau, Macau, Peoples R China
[2] Shenzhen Univ, Shenzhen, Peoples R China
[3] Univ North Carolina Chapel Hill, Chapel Hill, NC USA
[4] Univ Kassel, Kassel, Germany
[5] City Univ Macau, Fac Innovat & Design, KC Wong Bldg,Ave Padre Tomas Pereira Taipa, Macau, Peoples R China
来源：
JOURNAL OF PLANNING EDUCATION AND RESEARCH | 2023年 / 43卷 / 02期
关键词：
energy consumption; urban form; geomorphometry; microclimate; urban sustainability; ELECTRICITY CONSUMPTION; HEAT-ISLAND; STATISTICAL-ANALYSIS; MODEL; DENSITY; BUILDINGS; CITY; SIMULATION; EFFICIENCY; TRANSPORT;
D O I：
10.1177/0739456X19873382
中图分类号：
TU98 [区域规划、城乡规划];
学科分类号：
0814 ; 082803 ; 0833 ;
摘要：
Understanding the spatial pattern of energy consumption within buildings is essential to urban energy planning and management. This study explores the spatial complexity of residential energy usage intensity, with a focus on urban form and geomorphometry attributes. Using spatial regression models, we find that while vegetation and isolation have more local impact on energy intensity, urban porosity and roughness length have consistent spillover effects on building electricity usage intensity in Chicago. In addition, these relationships are seasonally varied. The results highlight the importance of spatially explicit policies and clear urban design and form frameworks for improving urban energy efficiency.
引用
收藏
页码：317 / 331
页数：15
相关论文
共 59 条
  • [1] Explaining the adoption of energy-efficient technologies in US commercial buildings
    Andrews, Clinton J.
    Krogmann, Uta
    [J]. ENERGY AND BUILDINGS, 2009, 41 (03) : 287 - 294
  • [2] Technology diffusion and energy intensity in US commercial buildings
    Andrews, Clinton J.
    Krogmann, Uta
    [J]. ENERGY POLICY, 2009, 37 (02) : 541 - 553
  • [3] [Anonymous], 2014, The R Foundation for Statistical Computing
  • [4] [Anonymous], THESIS
  • [5] Improving the prediction of UK domestic energy-demand using annual consumption-data
    Baker, Keith J.
    Rylatt, R. Mark
    [J]. APPLIED ENERGY, 2008, 85 (06) : 475 - 482
  • [6] BARLAG AB, 1991, ENERG BUILDINGS, V15, P291
  • [7] Urban greening to cool towns and cities: A systematic review of the empirical evidence
    Bowler, Diana E.
    Buyung-Ali, Lisette
    Knight, Teri M.
    Pullin, Andrew S.
    [J]. LANDSCAPE AND URBAN PLANNING, 2010, 97 (03) : 147 - 155
  • [8] Burghardt R., 2014, Development of an ArcGIS Extension to Model Urban Climate Factors (Doctoral dissertation)
  • [9] Spatio-temporal dimensions of child poverty in America, 1990-2010
    Call, Maia A.
    Voss, Paul R.
    [J]. ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE, 2016, 48 (01): : 172 - 191
  • [10] Development and validation of regression models to predict monthly heating demand for residential buildings
    Catalina, Tiberiu
    Virgone, Joseph
    Blanco, Eric
    [J]. ENERGY AND BUILDINGS, 2008, 40 (10) : 1825 - 1832
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