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Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics

Pan Lee (Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong)
Edwin H.W. Chan (Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong)
Queena K. Qian (Delft University of Technology, Delft, The Netherlands)
Patrick T.I. Lam (Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong)

Facilities

ISSN: 0263-2772

Article publication date: 12 March 2019

Issue publication date: 12 July 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.

Keywords

Acknowledgements

The authors gratefully acknowledge the Hong Kong Polytechnic University for providing funding to support this study via the General Research Fund of the Hong Kong SAR Government (Project Account Code: 152006/14E). The third author is thankful for the generous support of Delft Technology Fellowship (2014-2020).

Citation

Lee, P., Chan, E.H.W., Qian, Q.K. and Lam, P.T.I. (2019), "Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics", Facilities, Vol. 37 No. 11/12, pp. 860-878. https://doi.org/10.1108/F-05-2017-0051

Publisher

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Emerald Publishing Limited

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