TY - JOUR
T1 - A statistics-based method to quantify residential energy consumption and stock at the city level in China: The case of the Guangdong-Hong Kong-Macao Greater Bay Area cities
AU - Wang, Yousong
AU - Wu, Tongyuan
AU - Li, Hongyang
AU - Skitmore, Martin
AU - Su, Boya
N1 - Funding Information:
This work was supported by National Natural Science Foundation of China (Grant No. 71501074 ) , the “13th Five-Year” Plan of Philosophy and Social Sciences of Guangdong Province (2019 General Project) (Project No.: GD19CGL27 ) and the Fundamental Research Funds for the Central Universities (approval number 2019MS116 ; project number D2192640 ). Appendix Box 1 Sketch map of the availability of REC-related statistics by city. (Notes: 1. EBT denotes energy balance table. 2. Data Source: Statistical Yearbook of each city and China Urban Construction Statistical Yearbook.) Box 1
Publisher Copyright:
© 2019 Elsevier Ltd
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - The residential sector is a substantial consumer of energy worldwide, especially in China, and therefore a focus of energy conservation efforts. Although cities are basic executive units nowadays, their residential energy consumption (REC) is often overlooked. By revealing this research gap, we develop a REC calculation model at the city level (CRECM) and an improved residential stock turnover model (RSTM) to calculate the REC and residential stock of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) cities. Based on these two indicators, the REC intensity is quantified to measure residential energy efficiency. The results show that 11 GBA cities see a dramatic increase in REC over the past 16 years and REC intensities of most cities have plateaued out. The total REC of GBA is expected to rise until that of Guangzhou and Shenzhen reaches the peak. Also, the over residential stock of GBA has tended to saturation in recent years after significant growth, while some cities (i.e. Zhuhai, Huizhou, and Zhongshan) tend to increase. The gaps in REC among cities can be attributed to socio-economic factors (population, GDP, and residential stock) and building characteristics (unit area and construction vintage). Both CRECM and RSTM proposed in this study can provide robust data support for developing building energy efficiency policies for GBA cities as well as other cities across the country.
AB - The residential sector is a substantial consumer of energy worldwide, especially in China, and therefore a focus of energy conservation efforts. Although cities are basic executive units nowadays, their residential energy consumption (REC) is often overlooked. By revealing this research gap, we develop a REC calculation model at the city level (CRECM) and an improved residential stock turnover model (RSTM) to calculate the REC and residential stock of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) cities. Based on these two indicators, the REC intensity is quantified to measure residential energy efficiency. The results show that 11 GBA cities see a dramatic increase in REC over the past 16 years and REC intensities of most cities have plateaued out. The total REC of GBA is expected to rise until that of Guangzhou and Shenzhen reaches the peak. Also, the over residential stock of GBA has tended to saturation in recent years after significant growth, while some cities (i.e. Zhuhai, Huizhou, and Zhongshan) tend to increase. The gaps in REC among cities can be attributed to socio-economic factors (population, GDP, and residential stock) and building characteristics (unit area and construction vintage). Both CRECM and RSTM proposed in this study can provide robust data support for developing building energy efficiency policies for GBA cities as well as other cities across the country.
UR - http://www.scopus.com/inward/record.url?scp=85076516856&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2019.119637
DO - 10.1016/j.jclepro.2019.119637
M3 - Article
AN - SCOPUS:85076516856
SN - 0959-6526
VL - 251
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 119637
ER -