Maximilian Bock
University of Cambridge
Dr Maximilian Bock is a researcher at the University of Cambridge. A physicist by training, he has a professional background in natural materials for construction, life cycle assessments, and tools to inform early design phases for housing. Previously, he investigated use-case of engineered bamboo in the developing world as a high-performing building material. In 2014, he consulted for UN Habitat in Kenya on housing policy and tools, and is active contributor for SHERPA, a 10YFP funded housing design guide for the Global South. He is currently working at the Resource Efficiency Collective jointly with Granta Design on technological innovations that advance sustainable housing solutions and is an investigator on circular economy for the built environment.
If national and international CO2 emission targets are to be met, it is clear that the energy demands of buildings need to be reduced due to their large contribution to global emissions. However, devoid of any cost... [ view full abstract ]
If national and international CO2 emission targets are to be met, it is clear that the energy demands of buildings need to be reduced due to their large contribution to global emissions. However, devoid of any cost considerations, low-energy buildings will remain the exception rather than the rule for new building. Further, evidence from practice shows that despite best intentions of government schemes and building assessment tools to drive a reduction in energy, award-winning projects are not necessarily performing better in terms of overall life cycle energy consumption.
In the UK, sustainability briefs for construction projects are mandatory to encourage best practices and typically feature energy and emission targets to be met. However, tools to inform such decisions such as life cycle assessment or life cycle costing rely on completed design work to provide sufficient detail for calculations. This results in architects and engineers having to make critical design decisions regarding sustainability based on either past experience or good faith. Additionally, during pre-construction, quantity surveyors “optionengineer” specified materials for perceived equivalent products absent of any performance or energy evaluation that could verify equivalency.
To address these challenges, a design committee at the University of Cambridge conceived Energy Cost Metric (ECM) which seeks to bridge the performance gap between cost and energy considerations in a transparent and effective manner. The ECM relates the total energy to the building cost factored by the current or anticipated cost of energy. It is agnostic to the scale and detail of considered design options. It was put into immediate application at West Cambridge Development Site to guide design decisions from initial stage to construction.
The session presents this new metric to measure and evaluate building design options consistently across the design phase involving architects, engineers, quantity surveyors and contractors. We review different case studies prepared by industry partners Max Fordham, Grimshaw Architects, and Smith and Wallwork Engineers, using the ECM to provide quantitative measures for making key design decisions that will affect the overall cost and energy consumption of the project. To prevent the design process to drive unwanted outcomes that may be lower in overall energy at the expense of occupant comfort, explicit constraints are to be set and discussed.
Overall, the ECM provides a novel and meaningful approach to designers to achieve very-low energy designs at early stages of the design project. The work presented here serves a precedent for further investigations to capture the impact potential of the ECM. Key areas of further work revolve around tests on completed buildings compared to typical building data, in particular how predicted and measured energy data will be calculated, recorded and compared as the design and procurement progress.
• Sustainability and resilience metrics , • Business and industry practices / case studies , • Decision support methods and tools