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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.

The Emission Trading System has been promoted as a tool for providing financial and cost-effective incentives to carbon emitters to apply emission reduction measures. The mechanism of Emission Trading System has been applied in many energy-intensive industries such as electric power industry. However, it appears that Emission Trading System finds limited application in building sector due to the unique characteristics of buildings. This study presents an identification and analysis on the factors affecting the implementation of Emission Trading System in the building sector within the context of China. Research data are collected from semi-structured interviews with a group of carefully selected experts. As a result, fifteen representative factors have been identified, and discussions on their representativeness have been conducted. The intricate interrelationships between the identified factors have been examined based on a hierarchy structure established by using the Interpretive Structural Modeling method. Furthermore, these factors have been classified into four categories: autonomous factors, dependent factors, linkage factors, and driving factors, which is based on the calculation of the factors' driving/dependence power by applying the Matrice d’Impacts croises-multipication appliqué a classement (MICMAC) technique. This classification provides a different profile between individual factors from that by traditional study where the relative importance is generally given between factors. The findings on these factors provide valuable references for helping policy designers and practitioners adopt effective policies and measures to promote the development of ETS in the Chinese building sector. [ABSTRACT FROM AUTHOR]