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A Rapid Urban De-carbonization Scenario Analysis Tool

Allen, Andrew; Zakery, Sameh; Mao, Yong; Robinson, Darren

Authors

Andrew Allen

Sameh Zakery

YONG MAO yong.mao@nottingham.ac.uk
Associate Professor

Darren Robinson



Abstract

A rapid urban de-carbonization scenario analysis tool has been developed. The tool is able to efficiently and effectively generate and populate spatially resolved large scale building scenes, to generate XML input files for the building energy simulation engine CitySim [1], to quickly modify building thermal attributes and develop and analyze de-carbonization scenarios as snapshot modifications to the building scene. The tool has been developed as a series of plugins to the Quantum Geographical Information System (QGIS) [2] application, whereby it can make use of much of the QGIS existing functionality and software libraries. A tip to tail test of the tool is performed on a basic scenario.

Citation

Allen, A., Zakery, S., Mao, Y., & Robinson, D. (2017). A Rapid Urban De-carbonization Scenario Analysis Tool. Procedia Engineering, 198, 826-835. https://doi.org/10.1016/j.proeng.2017.07.133

Journal Article Type Article
Acceptance Date May 1, 2017
Online Publication Date Sep 11, 2017
Publication Date 2017
Deposit Date Oct 5, 2017
Publicly Available Date Oct 5, 2017
Journal Procedia Engineering
Print ISSN 1877-7058
Electronic ISSN 1877-7058
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 198
Pages 826-835
DOI https://doi.org/10.1016/j.proeng.2017.07.133
Public URL http://eprints.nottingham.ac.uk/id/eprint/46999
Publisher URL http://www.sciencedirect.com/science/article/pii/S1877705817329806?via%3Dihub
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
Additional Information This article is maintained by: Elsevier; Article Title: A Rapid Urban De-carbonization Scenario Analysis Tool; Journal Title: Procedia Engineering; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.proeng.2017.07.133; Content Type: article; Copyright: © 2017 Published by Elsevier Ltd.

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