Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China

Building lifetime and stock turnover are both key determinants in modelling building energy and carbon. However in China, aside from anecdotal claims that urban residential buildings are generally short-lived, there are no recent official statistics, and empirical data are extremely limited. We pres...

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Main Authors: Wei Zhou, Alice Moncaster, David M Reiner, Peter Guthrie
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/11/13/3720
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spelling doaj-291ab5a08c4440ce99e8fb38952484752020-11-24T21:54:39ZengMDPI AGSustainability2071-10502019-07-011113372010.3390/su11133720su11133720Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in ChinaWei Zhou0Alice Moncaster1David M Reiner2Peter Guthrie3Energy Policy Research Group, University of Cambridge, Cambridge CB2 1AG, UKDepartment of Engineering, University of Cambridge, Cambridge CB2 1PZ, UKEnergy Policy Research Group, University of Cambridge, Cambridge CB2 1AG, UKDepartment of Engineering, University of Cambridge, Cambridge CB2 1PZ, UKBuilding lifetime and stock turnover are both key determinants in modelling building energy and carbon. However in China, aside from anecdotal claims that urban residential buildings are generally short-lived, there are no recent official statistics, and empirical data are extremely limited. We present a system dynamics model where survival analysis is used to characterise the dynamic interplay between new construction, aging, and demolition of residential buildings in urban China. The uncertainties associated with building lifetime were represented using a Weibull distribution, whose shape and scale parameters were calibrated based on official statistics on floor area up to 2006. The calibrated Weibull lifetime distribution allowed us to estimate the dynamic stock turnover of Chinese urban residential buildings for 2007 to 2017. We find that the average lifetime of urban residential buildings was around 34 years, and the overall residential stock size reached 23.7 billion m<sup>2</sup> in 2017. The resultant age-specific sub-stocks provide a baseline for the overall stock, which&#8212;along with the calibrated Weibull lifetime distribution&#8212;can be used in further modelling and for analysis of policies to reduce the whole-life embodied and operational energy and CO<sub>2</sub> emissions in Chinese residential buildings.https://www.mdpi.com/2071-1050/11/13/3720building stocksurvival analysislifetime distributionsystem dynamics
collection DOAJ
language English
format Article
sources DOAJ
author Wei Zhou
Alice Moncaster
David M Reiner
Peter Guthrie
spellingShingle Wei Zhou
Alice Moncaster
David M Reiner
Peter Guthrie
Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
Sustainability
building stock
survival analysis
lifetime distribution
system dynamics
author_facet Wei Zhou
Alice Moncaster
David M Reiner
Peter Guthrie
author_sort Wei Zhou
title Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
title_short Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
title_full Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
title_fullStr Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
title_full_unstemmed Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
title_sort estimating lifetimes and stock turnover dynamics of urban residential buildings in china
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2019-07-01
description Building lifetime and stock turnover are both key determinants in modelling building energy and carbon. However in China, aside from anecdotal claims that urban residential buildings are generally short-lived, there are no recent official statistics, and empirical data are extremely limited. We present a system dynamics model where survival analysis is used to characterise the dynamic interplay between new construction, aging, and demolition of residential buildings in urban China. The uncertainties associated with building lifetime were represented using a Weibull distribution, whose shape and scale parameters were calibrated based on official statistics on floor area up to 2006. The calibrated Weibull lifetime distribution allowed us to estimate the dynamic stock turnover of Chinese urban residential buildings for 2007 to 2017. We find that the average lifetime of urban residential buildings was around 34 years, and the overall residential stock size reached 23.7 billion m<sup>2</sup> in 2017. The resultant age-specific sub-stocks provide a baseline for the overall stock, which&#8212;along with the calibrated Weibull lifetime distribution&#8212;can be used in further modelling and for analysis of policies to reduce the whole-life embodied and operational energy and CO<sub>2</sub> emissions in Chinese residential buildings.
topic building stock
survival analysis
lifetime distribution
system dynamics
url https://www.mdpi.com/2071-1050/11/13/3720
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