Constanza Molina
A data analysis of the Chilean housing stock and the development of modelling archetypes
Molina, Constanza; Kent, Michael; Hall, Ian; Jones, Benjamin
Authors
Michael Kent
Professor IAN HALL IAN.HALL@NOTTINGHAM.AC.UK
PROFESSOR OF MOLECULAR MEDICINE
Dr BENJAMIN JONES Benjamin.Jones@nottingham.ac.uk
ASSOCIATE PROFESSOR
Abstract
Chile is a South American country experiencing greater social and economic development than the majority of its neighbours and whose economy is transitioning from developing to developed status. It is committed to reduce its greenhouse gas (GHG) emissions by 35–45% by 2030, requiring national energy demand reduction. Chile's housing stock is responsible for 15% of its total final energy consumption and so its Government is regulating the construction of new dwellings, although it is difficult to know if this policy will succeed or lead to unintended consequences affecting energy demand, GHG emissions, and occupant health. Measuring the effects in situ is often time and cost prohibitive and so the simulation of archetypal buildings is a common method of investigation. A range of data sources, such as censuses and building permits, are used to develop archetypal Chilean houses with statistically significant representative values for design parameters related to energy demand and indoor air quality. It finds that 496 archetypes can represent 100% of the Chilean housing stock and only 90 can represent 95% of the stock. The archetypes can be used to predict and evaluate the impacts of policies on indoor air quality and the energy demand of a stock of houses, or to guide future data gathering exercises. The data analysis highlights knowledge gaps in categorical descriptors and occupant behaviours, and poor granularity of physical data. These gaps should be filled by augmenting national surveys and complimented by field work.
Citation
Molina, C., Kent, M., Hall, I., & Jones, B. (2020). A data analysis of the Chilean housing stock and the development of modelling archetypes. Energy and Buildings, 206, Article 109568. https://doi.org/10.1016/j.enbuild.2019.109568
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 27, 2019 |
Online Publication Date | Nov 1, 2019 |
Publication Date | Jan 1, 2020 |
Deposit Date | Nov 20, 2019 |
Publicly Available Date | Nov 2, 2020 |
Journal | Energy and Buildings |
Print ISSN | 0378-7788 |
Electronic ISSN | 1872-6178 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 206 |
Article Number | 109568 |
DOI | https://doi.org/10.1016/j.enbuild.2019.109568 |
Keywords | Indoor air quality; Energy demand reduction; Carbon emissions; Climate change; Regulation; Housing typologies |
Public URL | https://nottingham-repository.worktribe.com/output/3342589 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0378778819318699 |
Additional Information | This article is maintained by: Elsevier; Article Title: A data analysis of the Chilean housing stock and the development of modelling archetypes; Journal Title: Energy and Buildings; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.enbuild.2019.109568; Content Type: article; Copyright: © 2019 Elsevier B.V. All rights reserved. |
Contract Date | Nov 20, 2019 |
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