Cross disciplinary confusion - how do you explain urban building models to a social scientist?

GEMDev is an inherently multi-disciplinary project with researchers from engineering, architecture and social science backgrounds as well as NGO partners working directly with marginalised communities in Lima and Ahmedabad. Although our goals are aligned, developing a shared understanding of the methods and tools we each use has been a vital step in the project to make sure we get the maximum benefit from each aspect. One of the biggest challenges within the team has been trying to move beyond casual references to “the model” to a deeper understanding of how that model is constructed and how its outputs can be made as useful as possible for the communities we are working with.

Worldwide, buildings are responsible for over one-third of global final energy consumption and nearly 40% of total direct and indirect CO2 emissions, figures which are continuing to rise.

Developing detailed plans to reduce emissions is a key priority for cities world-wide. While it is easy to work how to reduce emissions for an individual building, to generate solutions for a city of millions of buildings, cities need to:

  • Identify the key drivers for building energy consumption
  • Understand how a diverse stock of existing buildings can best be modified to reduce carbon emissions.
  • Evaluate the potential for renewable energy systems, where and how they can be best implemented
  • Identify the skills which are needed to deliver the transformation of the city’s buildings.

Building Energy Models use physics to calculate how much energy is used in a building for heating, cooling, lighting, cooking and powering equipment. How much energy is used depends on the needs and activities of the people using the buildings, the efficiency of the appliances they use, the climate outside the buildings, size, orientation and how good or bad the buildings are at retaining heat. Urban building energy models calculate the energy consumption of whole neighbourhoods or cities by evaluating the energy flows into and out of every building.

Urban Building Energy Models use large urban datasets to create models of all the buildings in the area they cover, using data about building age, use, location, size and orientation to calculate heat flows and energy consumption. Developing detailed models of all the buildings in even a small city can be a very time-consuming task. To deal with this, UCL have developed SimStock – a modelling platform which combines geometrical information about the size and orientation of buildings, with details about the materials used to construct them, the systems and equipment in them and the patterns of energy usage of their occupants. SimStock automatically generates inputs for each individual building and uses EnergyPlus, a state-of-the-art energy analysis and simulation programme to calculate energy flows. Energy consumption for a whole city can be calculated hour by hour together with internal temperatures which allows overheating risks to be assessed. So far SimStock has been used to develop models for parts of London, Ahmedabad, Beijing and Cahors.

Slums and informal settlements are rarely included in urban building energy models, largely because their energy consumption is low and their built environment is complex and hard to characterise, but these communities are typically the most vulnerable to impacts of climate change and least able to bear the costs, both of energy and adaptation, meaning planning for their needs is a critical issue. In addition, while the capacity of marginalised individuals to act to reduce emissions and increase climate change resilience is low, the collective capacity of communities is often underestimated. UBEMs offer the potential for communities living in these areas to benefit from identifying collective actions to reduce emissions, improve living conditions and develop the skills needed to effect the transformation.

Developing this shared understanding has taken considerable time for the project team, and there is much work still to be done to ensure that the information and tools we produce have the maximum impact for the communities they are based on.

An important first step in the modelling work will be moving beyond the simple representations of nuclear families that are typical in urban building energy models to capture the complexity and diversity of energy behaviours seen in the communities we are working with.