Print Email Facebook Twitter Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics Title Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics Author Lee, Pan (The Hong Kong Polytechnic University) Chan, Edwin H.W. (The Hong Kong Polytechnic University) Qian, QK (TU Delft Housing Quality and Process Innovation) Lam, Patrick T.I. (The Hong Kong Polytechnic University) Date 2019 Abstract Purpose: Design teams have difficulties in assessing building carbon emissions at an early stage, as most building energy simulation tools require a detailed input of building design for estimation. The purpose of this paper is to develop a user-friendly regression model to estimate carbon emissions of the preliminary design of office buildings in the subtropics by way of example. Five sets of building design parameters, including building configuration, building envelope, design space conditions, building system configuration and occupant behaviour, are considered in this study. Design/methodology/approach: Both EnergyPlus and Monte Carlo simulation were used to predict carbon emissions for different combinations of the design parameters. A total of 100,000 simulations were conducted to ensure a full range of simulation results. Based on the simulation results, a regression model was developed to estimate carbon emissions of office buildings based on preliminary design information. Findings: The results show that occupant density, annual mean occupancy rate, equipment load, lighting load and chiller coefficient of performance are the top five influential parameters affecting building carbon emissions under the subtropics. Besides, the design parameters of ten office buildings were input into this user-friendly regression model for validation. The results show that the ranking of its simulated carbon emissions for these ten buildings is consistent with the original carbon emissions ranking. Practical implications: With the use of this developed regression model, design teams can not only have a simple and quick estimation of carbon emissions based on the building design information at the conceptual stage but also explore design options by understanding the level of reduction in carbon emissions if a certain building design parameter is changed. The study also provides recommendations on building design to reduce carbon emissions of office buildings. Originality/value: Limited research has been conducted to date to investigate how the change of building design affects carbon emissions in the subtropics where four distinct seasons lead to significant variations of outdoor temperature and relative humidity. Previous research also did not emphasise on the impact of high-rise office building designs (e.g. small building footprint, high window-to-wall ratio) on carbon emissions. This paper adds value by identifying the influential parameters affecting carbon emissions for a high-rise office building design and allows a handy estimate of building carbon emissions under the subtropical conditions. The same approach may be used for other meteorological conditions. Subject Building designCarbon emissionOffice building To reference this document use: http://resolver.tudelft.nl/uuid:47946dfa-1baa-4271-95f6-046445a433ff DOI https://doi.org/10.1108/F-05-2017-0051 Embargo date 2020-02-05 ISSN 0263-2772 Source Facilities, 37 (11-12), 860-878 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2019 Pan Lee, Edwin H.W. Chan, QK Qian, Patrick T.I. Lam Files PDF 10_1108_F_05_2017_0051.pdf 456.6 KB Close viewer /islandora/object/uuid:47946dfa-1baa-4271-95f6-046445a433ff/datastream/OBJ/view