China's building stock estimation and energy intensity analysis. (10th January 2019) - Huo, Tengfei; Cai, Weiguang; Ren, Hong; Feng, Wei; Zhu, Minglei; Lang, Ningning; Gao, Jingxin
Abstract: Reliable and objective data regarding building stock is essential for predicting and analyzing energy demand and carbon emission. However, China's building stock data is lacking. This study proposes a set of China building floor space estimation method (CBFSM) based on the improved building stock turnover model. Then it measures China's building stocks by vintage and type from 2000 to 2015, as well as building energy intensity (national level and provincial level) and energy-efficient buildings. Results showed that total building stocks increased significantly, rising from 35.2 billion m 2 in 2000 to 63.6 billion m 2 in 2015, with the average growth rate 4.0%. The deviations were well below 10% by comparing with China Population Census, which validated the reliability of CBFSM and the results. As for energy intensity, urban dwellings and rural dwellings showed relatively stable and increasing trend respectively. The commercial building energy intensity saw a downward trend during "12th Five Year Plan" period. This indicated the effectiveness of building energy efficiency work for commercial buildings since 2005.38.6 billion m 2 residential dwellings and 5.7 billion m 2 commercial buildings still need to be retrofitted in future. CBFSM can overcome shortages in previous studies. It can also provide Chinese government with technical support and data evidence to promote the building energy efficiency work. Graphical abstract: The building stock in China's different provinces and climate zones in 2015. Image Highlights: Proposed a China building floor space estimation method (CBFSM) based on improved building stock turnover model. Estimated China's building stocks by type and vintage from 2000 to 2015 using CBFSM. Calculated the building energy intensity at the national level and provincial level. Estimated the size of the energy efficient buildings in China. Validated the results of study by comparing with the data from China Population Census; the deviations are well below 10%.