Metrics of urban morphology and their impact on energy consumption: A case study in the United Kingdom

Abstract Energy policies implemented by local authorities and targeted at the domestic sector have focussed on interventions, which are usually selected after an optimisation procedure. This paper identifies differences and similarities between three Medium Layer Super Output Area (MLSOA) districts in the United Kingdom (UK) and draws conclusions which prove to be useful to interpret other districts in the city and provide general rules for energy efficiency measures and distributed supply interventions in Newcastle upon Tyne, UK, and potentially beyond. The core argument aims at provide an important link between the energy-reducing and energy-increasing effects of four urban morphology characteristics in ‘place-specific’ neighbourhoods. Our methodology explores the potential application of the close relation between four urban morphological characteristics and the spatial aggregated building energy end-use in the roll-out strategy of interventions. Our findings first indicate that the combination of shape and size of continuous building classes (in a building class the main residential buildings are grouped by their age and building type) and their extent using patch areas potentially simplify retrofit campaigns. We argue that the whole continuous building class influences the building's thermal mass (the building massing) and their extent (the patch area or patch in short) and these are better descriptors for the energy use in the occupational phase of a building. Second, the building massing and the plot ratio (the ratio of the building floor area to the land area in a given territory) are a better descriptors of building density/mixing of land use and built form leading to the potential use of adequate distributed energy supply. Third, the way in which social and economic factors interact to shape area-based of household energy consumption leads to a possible better spatially-enabled policies for low income families; and fourth, the layout and orientation design of the neighbourhood may identify municipal sites for potential renewable energy projects. The use of the building massing and patch areas as spatial cluster operators simplify the complexity of aggregated building energy consumption by representing its spatial incidence through a smooth continuous surface. Additionally, building classes and its patch area extent show notable differences across different sub-city areas. Furthermore, the greater the number of building classes, the more diverse is the socio-economic make-up of a sub-city area.

[1]  R. Reulke,et al.  Remote Sensing and Spatial Information Sciences , 2005 .

[2]  S V Subramanian,et al.  Comparison of a spatial perspective with the multilevel analytical approach in neighborhood studies: the case of mental and behavioral disorders due to psychoactive substance use in Malmo, Sweden, 2001. , 2005, American journal of epidemiology.

[3]  Milena Büchs,et al.  Who emits most? Associations between socio-economic factors and UK households' home energy, transport, indirect and total CO2 emissions , 2013 .

[4]  R. B. Hirematha,et al.  Decentralized energy planning ; modeling and application — a review , 2006 .

[5]  Clarissa Binkley,et al.  Correlating energy consumption with multi-unit residential building characteristics in the city of Toronto , 2013 .

[6]  Carlos Calderon,et al.  Data availability and repeatability for urban carbon modelling: a CarbonRouteMap for Newcastle upon Tyne , 2012 .

[7]  Philip James,et al.  A GIS domestic building framework to estimate energy end-use demand in UK sub-city areas , 2015 .

[8]  Michael O. Rodgers,et al.  Urban Form and Thermal Efficiency: How the Design of Cities Influences the Urban Heat Island Effect , 2001 .

[9]  Enrique Kremers,et al.  Towards a 3d Spatial Urban Energy Modelling Approach , 2013 .

[10]  Thomas Behr,et al.  Topological relationships between complex spatial objects , 2006, TODS.

[11]  Lamia Kamal-Chaoui,et al.  Competitive Cities and Climate Change , 2009 .

[12]  May,et al.  A Concise Course in Algebraic Topology , 1999 .

[13]  Philipp Rode,et al.  Cities and Energy: Urban Morphology and Residential Heat-Energy Demand , 2014 .

[14]  R. Camagni,et al.  Urban mobility and urban form: the social and environmental costs of different patterns of urban expansion , 2002 .

[15]  K. Steemers Energy and the city: density, buildings and transport , 2003 .

[16]  Koen Steemers,et al.  Modelling domestic energy consumption at district scale: A tool to support national and local energy policies , 2011, Environ. Model. Softw..

[17]  B. Joerges,et al.  Energy conservation programs for consumers: A comparative analysis of policy conflicts and program response in eight western countries , 1983 .

[18]  Mike Coombes,et al.  Public Policy and Population Distribution: Developing Appropriate Indicators of Settlement Patterns , 2001 .

[19]  Guglielmina Mutani,et al.  The role of urban form and socio-economic variables for estimating the building energy savings potential at the urban scale , 2015 .

[20]  R. Ewing,et al.  The impact of urban form on U.S. residential energy use , 2008 .