Document Type

Theses, Ph.D

Disciplines

2.1 CIVIL ENGINEERING

Publication Details

A thesis submitted for the degree of Doctor of Philosophy (PhD) submitted on Technological University Dublin, 2024.

Abstract

This work is centred around the global shift towards a post-fossil-fuel era, driven by climate change. The research is motivated by the urgent need to facilitate this transition, specifically focusing on the non-domestic building sector, which contributes in the order of 10 % [233] of global greenhouse gas emissions. The study aims to bridge the research gap in openly available, commonly accepted, simple-to-understand, validated and/or verified models and representative data sets of non-domestic building stocks that can be used to guide policymakers towards achieving climate neutrality. The main research objective is to create a life-cycle methodology and tool for modelling non-domestic buildings. Given the scale of this undertaking, this study focuses on the operational life cycle phase, given its relative importance to overall building emissions. The first step in the methodological approach to achieve the aims is understanding the current state-of-the-art in building stock modelling within a lifecycle context and identifying the most suitable methodologies and tools for the nondomestic sector. This is realized by undertaking, for the first time, a structured literature review on non-domestic building stock models in a life-cycle context. User needs, mostly neglected in building stock model development, are also taken into account through a user requirements elicitation process. The second methodological step involves acquiring, cleaning, imputing, and pre-processing a high-quality dataset necessary for operational non-domestic stock modelling, verification, and validation. Following a novel geo data based approach the German non-domestic building stock is surveyed, providing the data basis for the later simulation. The imputation process and resulting imputation models, representative of the German non-domestic building stock, are further contributing to knowledge. As a result, a large representative data set containing energy-relevant building attributes for the simulation of the German nondomestic building stock is created for the first time.

DOI

https://doi.org/10.21427/0fwj-6q10

Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

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