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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 m2 in 2000 to 63.6 billion m2 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 m2 residential dwellings and 5.7 billion m2 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.

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.

Social progress and economic development has resulted in the need to focus on the impacts of building microenvironment on the energy consumption in office buildings. The concept of a building's microenvironment was introduced to understand the local microclimate around a building that is formed by the surrounding urban green spaces, the distribution of roads, and building proximity. For this research, we adopted a regression analysis to quantify the impacts of building microenvironment on energy consumption in office buildings. Taking the government office buildings of Guangdong Province as an example, we measured the building microenvironment through the urban green space density, road density, and number of points of interest (POI) around the buildings. The results showed that when the green space density increased by one unit, the energy consumption in government office buildings was reduced by 0.277%. Moreover, an increase of 1% in road density and in the number of POI increased the energy consumption in government office buildings by 0.288% and 0.048%, respectively. Furthermore, we discussed the heterogeneous impacts of building microenvironment on the energy consumption in government office buildings at varying scale levels. Green space and road density had less impact on the energy consumption in larger buildings, whereas the number of POI had no significant impact on small-scale buildings but did have a significant impact on large-scale buildings. There were also some limitations in the study. The data were limited to government office buildings, and did not include panel data, as well as it lacked building characteristics such as orientation, floor height, and building materials. In addition, it was impossible to evaluate the impacts of meteorological factors such as wind speed and thermal radiation on energy consumption in buildings. Nonetheless, our study demonstrates that energy-aware urban planning and design have the potential to unlock energy efficiency for cities worldwide. [ABSTRACT FROM AUTHOR]

Soaring building heating energy consumption (BHEC), along with rising income, is threatening carbon abatement efforts. However, the influencing mechanism of income on BHEC remains unclear. This study establishes a theoretical model of the impact of income on BHEC from three perspectives: building physical characteristics, building use characteristics and energy-consuming equipment characteristics. Then, we adopt a stepwise hierarchical regression method to examine the direct and intermediary effects between income and BHEC using microdata from 662 households in Chongqing, China. The results show that household income, residential building floor space, the amount of heating equipment, building energy efficiency standards, and the heating method significantly impact BHEC. Moreover, the direct effect of income on BHEC is up to 84%. The amount of heating equipment and residential building floor space are both strong intermediaries between income and BHEC, contributing 18.8% and 15.8%, respectively. The heating method is a weak intermediary, only contributing approximately 1% of the impact. Overall, this study can promote the development of the related theory of BHEC and provide a reference for the government to implement more effective energy-efficient policies on the local scale and even on the national and global scales. • A splitting model-based calculation method is developed to estimate heating energy consumption • A theoretical model is established to examine the impact of income on heating energy use • The impact of income on heating energy consumption is examined with micro-evidence • Income affects heating energy use through two paths of direct and indirect effects • The number of heating equipment and floor space are both strong mediating variables [ABSTRACT FROM AUTHOR]

Urbanization has an important impact on building energy consumption. Unfortunately, whether the later-urbanized provincial regions are more energy-efficient than those early-urbanized regions in the building sector is still unclear. This study innovatively adopts the difference-in-differences (DID) model to examine the event effect of urbanization on building energy intensity with China's provincial evidence from 2000–2015. Moreover, its influence mechanism is identified with the mediating effect model. Results demonstrate that: (1) The building energy intensity is higher in provincial regions where the urbanization rate reached 45% earlier, indicating that the later-urbanized regions are more energy-efficient. (2) Considering heterogeneity, the event of urbanization rate reaching 45% contributes positively to building energy intensity in the eastern and central regions, but the effect in the western region is insignificant. This can further validate the later-mover advantage of the urbanization. (3) Regarding influence mechanism, urbanization can drive building energy intensity by increasing the proportion of the tertiary industry and population density or reducing the proportion of building coal consumption and the plot ratio of the urban area. This study can facilitate the related theoretical and practical exploration of the event effect of urbanization on energy consumption, which is conducive to formulating differentiated energy-conservation strategies. [Display omitted] • The DID model is applied to explore the event effect of urbanization on the building energy intensity. • The effect of urbanization on building energy intensity is explored considering regional heterogeneity. • The influence mechanism of urbanization on building energy consumption is investigated. • Later-urbanized regions are more energy-efficient in the building sector. • Urbanization can improve building energy intensity by potential mediating variables. [ABSTRACT FROM AUTHOR]