Greenhouse gas emissions originating from the built environment play a significant role towards climate change. Carefully planning the future of the building sector is key to mitigating these emissions. Addressing this problem by using a predictive approach may miss possible futures that cannot be anticipated. Using explorative scenarios to perform futures analysis helps widen the range of futures taken into account, which minimises this risk. Tools that use scenarios to help study the resilience of sustainable solutions for the UK urban environment are already available. However, they do not facilitate in-depth analysis of future household energy demand. This paper considers how one such tool, ‘Designing Resilient Cities’ (DRC), could be modified appropriately. It includes (a) a series of indicators representing factors affecting the energy demand in dwellings and (b) their characteristics for each scenario to complement the narratives in DRC. As a case study to validate these additions, the resilience of a recommendation to decrease domestic electricity consumption is evaluated.
Article navigation
1 August 2020
Research Article|
December 05 2019
Adapting futures scenarios to study UK household energy demand Available to Purchase
Miquel Banchs-Piqué, Lic (BSc+MSc), MSc
;
School of Civil Engineering and Surveying, University of Portsmouth, Portsmouth, UK
(corresponding author: miquel.banchs-pique@port.ac.uk)
Search for other works by this author on:
David J Hutchinson, PhD
;
David J Hutchinson, PhD
Innovation and Impact Development Manager
Faculty of Technology, University of Portsmouth, Portsmouth, UK
Search for other works by this author on:
Victor M Becerra, BEng, MSc, PhD, Sen. Mem. IEEE, CEng, FIET, Sen. Mem. AIAA
;
Victor M Becerra, BEng, MSc, PhD, Sen. Mem. IEEE, CEng, FIET, Sen. Mem. AIAA
Professor
School of Engineering, University of Portsmouth, Portsmouth, UK
Search for other works by this author on:
Mark Gaterell, BEng, MPhil (Cantab), PhD, DIC, CEnv, WCIWEM
Mark Gaterell, BEng, MPhil (Cantab), PhD, DIC, CEnv, WCIWEM
Professor
School of Civil Engineering and Surveying, University of Portsmouth, Portsmouth, UK
Search for other works by this author on:
(corresponding author: miquel.banchs-pique@port.ac.uk)
Publisher: Emerald Publishing
Received:
November 14 2018
Accepted:
October 23 2019
Online ISSN: 1751-7680
Print ISSN: 1478-4629
ICE Publishing: All rights reserved
2020
Proceedings of the Institution of Civil Engineers - Engineering Sustainability (2020) 173 (5): 241–256.
Article history
Received:
November 14 2018
Accepted:
October 23 2019
Citation
Banchs-Piqué M, Hutchinson DJ, Becerra VM, Gaterell M (2020), "Adapting futures scenarios to study UK household energy demand". Proceedings of the Institution of Civil Engineers - Engineering Sustainability, Vol. 173 No. 5 pp. 241–256, doi: https://doi.org/10.1680/jensu.18.00057
Download citation file:
Suggested Reading
Effects of ‘green transport’ on leisure behaviour in cities
Proceedings of the Institution of Civil Engineers - Transport (May,2016)
Stakeholders’ relevance in sustainable residential property development
Smart and Sustainable Built Environment (January,2020)
Life-cycle assessment of carbon dioxide emissions of asphalt pavements in China
Proceedings of the Institution of Civil Engineers - Engineering Sustainability (September,2019)
Impact of particulate matter and dust on photovoltaic systems in Shanghai, China
Proceedings of the Institution of Civil Engineers - Energy (September,2020)
Performance and emissions of spark-ignition engines fuelled with petrol and methane
Proceedings of the Institution of Civil Engineers - Energy (January,2021)
Related Chapters
Implementation of energy saving initiatives in design review
Crossrail Project: Infrastructure design and construction
Uncertainties in the design of ground heat exchangers
ICE Themes Geothermal Energy, Heat Exchange Systems and Energy Piles
The role of ground conditions on energy tunnels’ heat exchange
ICE Themes Geothermal Energy, Heat Exchange Systems and Energy Piles
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
