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As the pillar industry of the national economy, the construction industry contributes to economic growth while consuming large amounts of energy and generating carbon emissions. This study adopted the generalized Divisia index method (GDIM) to decompose carbon emissions in the construction industry (CECI) of China and its 30 provinces. A decoupling effort index based on factor decomposition was constructed to analyze the drivers of changes in the CECI and decoupling states during 2000–2020. The results were as follows. (1) The output scale was the main driver for increasing CECI, whereas the carbon intensities of area and output were the largest contributors to decreasing CECI. (2) The national construction industry showed expansive negative decoupling during the 10th–13th FYPs (Five-Year Plans). The decoupling states of provinces showed significant spatial and temporal differences, with most provinces showing negative decoupling and the number of decoupled provinces peaking in the 12th FYP. (3) The scale effect was the key inhibiting factor in the decoupling process of most provinces, while the intensity effect was the main promoting factor, and the efficiency effect was weak. The inhibitory effect of scale gradually weakened, while the promoting effect of intensity increased. Overall, this study expands on current research related to the driving factors of CECI and provides valuable insights into the low-carbon development of the construction industry in other emerging countries. • A GDIM-based decoupling analysis was applied to the construction industry. • The output scale and area scale were the key factors that increased carbon emissions. • Most provincial construction industries showed negative decoupling. • Efforts to promote decoupling should focus more on intensity and efficiency effects. [ABSTRACT FROM AUTHOR]

This study measures the "real" total-factor energy efficiency (TFEE) of the construction industry with data from 30 Chinese provinces (excluding Tibet) from 2006 to 2015 using the DEA model combined with the TFEE algorithm. The floor space under construction is considered to be an output indicator in addition to the traditional economic output under the TFEE framework. Next, the spatial distribution of the TFEE of construction industry among those provinces is detected and possible reasons are analyzed. Results indicate that, most of Chinese provincial regions are energy inefficient in construction industry during the research period. Conversely, the three provinces of Beijing, Hainan and Zhejiang have optimal efficiency, which constitutes the efficiency frontier of energy consumption throughout China. There exists divergence among 30 provinces and three regions as for TFEE, but the divergence decreases and manifests the convergence feature. Moreover, among the three main regions, central and eastern regions' TFEE of the construction industry are higher than the figure for the western region. By comparison, we found that the TFEE evaluation considering floor space under construction is more accurate and rational than without considering the floor space. On the basis of these findings, some policy implications are provided for improving Chinese energy efficiency, especially for less developed regions. [ABSTRACT FROM AUTHOR]

China's energy consumption in the building sector (BEC) is not counted as a separate type of energy consumption, but divided and mixed in other sectors in China's statistical system. This led to the lack of historical data on China's BEC. Moreover, previous researches' shortages such as unsystematic research on BEC, various estimation methods with complex calculation process, and difficulties in data acquisition resulted in “heterogeneous” of current BEC in China. Aiming to these deficiencies, this study proposes a set of China building energy consumption calculation method (CBECM) by splitting out the building related energy consumption mixed in other sectors in the composition of China Statistical Yearbook-Energy Balance Sheet . Then, China's BEC from 2000 to 2014 are estimated using CBECM and compared with other studies. Results show that, from 2000 to 2014, China's BEC increased 1.7 times, rising from 301 to 814 million tons of standard coal consumed, with the BEC percentage of total energy consumption stayed relatively stable between 17.7% and 20.3%. By comparison, we find that our results are reliable and the CBECM has the following advantages over other methods: data source is authoritative, calculation process is concise, and it is easy to obtain time series data on BEC etc. The CBECM is particularly suitable for the provincial government to calculate the local BEC, even in the circumstance with statistical yearbook available only. [ABSTRACT FROM AUTHOR]