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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.

Equitable and effective allocation of provincial carbon allowances is the key to achieving carbon peaking and carbon neutrality targets and addressing the prominent issue of resource and environmental constraints, while reasonable coupling of equity and efficiency is its prerequisite. The study first assessed the effectiveness of the mainstream allocation methods when applied to the building sector. Then, Monte Carlo simulation is used to properly couple the principles of equity and efficiency in the process of carbon allowance allocation in the building sector, and on this basis, a novel Allocation method of Regional Carbon Allowance in Building sector (ARCAB) is constructed to provide an inter-provincial allocation scheme of building carbon emission allowances in 2030 for China. The results show that the mainstream allocation methods are not applicable to the building sector, and their allocation results often appear the phenomenon of "low-hanging fruit" or "high-hanging fruit". In addition, the coupling degree of equity-efficiency is 12% in China's 2030 allocation scheme, indicating that provincial governments should formulate more stringent carbon reduction policies to achieve this goal. The proposed ARCAB and our findings can assist decision-makers to formulate reasonable carbon allowances and differentiated emission-reduction strategies and will be of national and global significance. • Propose the criteria to judge the effectiveness of building carbon allowances. • Mainstream carbon allowance allocation methods do not apply to the building sector. • Propose an Allocation method of Regional Carbon Allowance in Building sector (ARCAB). • Focus on carbon reduction in commercial buildings in China. [ABSTRACT FROM AUTHOR]

Clarifying the critical driving factors and the driving mechanism for building carbon emissions is fundamental for carbon peak and carbon neutrality prediction. This study comprehensively identifies 23 representative factors using the literature research and questionnaire survey method. Then, by coupling the decision-making trial and evaluation laboratory (DEMATEL) method and the interpretive structural model (ISM), an integrated DEMATEL-ISM model is developed. The proposed model is further employed to quantify the causal relationships among the factors and establish a multi-level recursive structure model to determine the action mechanism of those drivers. The results show that the 11 cause factors, 12 effect factors and the three most important factors including the economic development level, building end-use energy consumption and end-use energy intensity are identified based on the calculated cause and center degree. Based on the obtained hierarchy, the 23 factors are divided into six levels, among which the population factors, the economic development, the urbanization level and the share of the tertiary sector are the root factors leading to the building carbon emissions. In comparison, policy factors are the most critical inhibiting factors. This study can not only promote the theory and model development for the driving mechanism of carbon emissions, but also help decision-makers develop scientific carbon reduction strategies. • Establishes an integrated DEMATEL-ISM model by coupling the DEMATEL method with the ISM. • Identifies the representative factors affecting the building carbon emissions from the systematic perspective. • Explores the significance of the factors and their intricate interactive mechanism. • Population factors, socio-economic development, urbanization level and the tertiary sector share are the fundamental factors. • Policy factors are the most critical inhibiting factors. [ABSTRACT FROM AUTHOR]

Carbon mitigation effectiveness in the building sector profoundly determines the achievement of the "Dual carbon" target. However, the timetable and roadmap for the building sector to achieve such a target are still lacking. This study constructs a STIRPAT-PLS model framework to clarify the impact of the key factors from various dimensions on building carbon emissions across sub-sectors. Then, a dynamic scenario simulation model is established and applied in China to explore the dynamic evolutionary paths, and the timetable and roadmap are ultimately formulated. The results show that building sector will probably peak at 2.99 (± 0.09) Gt CO 2 in 2036 (± 1). Rural residential buildings will peak earliest in 2026 (± 1), followed by urban residential and commercial buildings: in 2036 (± 2) and 2038 (± 1). Achieving carbon neutrality will require the building sector to peak its carbon emissions in 2026 with 2.16–2.40 Gt CO 2. The remaining 0.56–0.81 Gt CO 2 by 2060 will be offset by negative carbon technologies. Dynamic sensitivity analysis shows that building floor space per capita and energy intensity significantly promote the emission peaks, and population and building floor space per capita markedly impact the peaking times. This study can promote the development of the theory and model for carbon emissions prediction. It can also offer a scientific basis for governments to set effective carbon-reduction targets and paths. [Display omitted] • Constructing a STIRPAT-PLS model to clarify the impact of critical factors on building carbon emissions. • Establishing a dynamic scenario simulation model by combining the Monte Carlo simulation and scenario analysis. • Building sector will probably peak at 2.99 (± 0.09) Gt CO 2 in 2036 (± 1). • Achieving carbon neutrality requires the building sector to peak its carbon emissions in 2026 with 2.16–2.40 Gt CO 2. • Building floor space per capita and energy intensity significantly promote the emission peaks. [ABSTRACT FROM AUTHOR]

Clarifying the spatial association network of provincial building carbon emissions and its influential drivers is profoundly significant for transregional collaborative emission reduction and regionally-coordinated development. This study adopts the social network analysis method to investigate the network structure characteristics of carbon emissions in the building sector based on China's provincial-level evidence from 2000 to 2018. Then, the quadratic assignment procedure is further utilized to examine the driving factors. The results demonstrate that building carbon emissions in China take the form of a network structure. From 2000 to 2018, the relevance and stability of the spatial associations gradually strengthened. Shanghai, Jiangsu, Tianjin, Beijing and Zhejiang are in the center of the spatial association network and play a vital part in the network. The network of carbon emissions in the building sector can be classified into four plates: the main inflow plate, main outflow plate, bidirectional spillover plate and agent plate. Geographical adjacency, economic development level, energy intensity and industrial structure are significantly correlated with building carbon emissions. The urbanization level has no significant influence on the spatial correlations of building carbon emissions. This study is conducive to formulating energy conservation policies and promoting transregional collaborative emission reductions. [Display omitted] • Adopting the SNA method to explore the spatial network structure of China's building carbon emissions. • Using the QAP method to determine the factors affecting the spatial correlation network of building carbon emissions. • The relevance and stability of the spatial associations gradually strengthened. • Shanghai, Jiangsu, Tianjin, Beijing and Zhejiang occupy a central position in the network. • Spatial adjacency, economic development, energy intensity and industrial structure significantly affected spatial network. [ABSTRACT FROM AUTHOR]

• Establishes a comprehensive framework to explore the multiple-effects exerted by urbanization on future building carbon emissions. • Constructs a carbon emission dynamic scenario simulation model by combining the extended Kaya identity and Monte Carlo simulation. • The building sector will reach its peak at 3.09 (±0.36) Bt CO 2 in 2037 (±4). • Rural residential building sector will be the first to reach its energy and emission peak. • Economic urbanization and space urbanization exert major promoting effects on the peaking time and emission peaks of building carbon emissions. The accelerating urbanization has posed great challenges to China's carbon-mitigation efforts and global climate change response. However, how does the urbanization process impact the peak of future carbon emissions from buildings is still unclear. This study first establishes a comprehensive urbanization framework from three dimensions. Then, a dynamic scenario simulation model is innovatively constructed by combining the extended Kaya identity and Monte Carlo simulation approach to explore future dynamic evolution trajectory, possible peaks and peaking time of China's building carbon emissions from 2000 to 2050, considering the uncertainties of factors. Finally, dynamic sensitivity analysis is performed to investigate the contributions of different dimensions of the urbanization. Results show that under the business-as-usual scenario, the rural residential building sector will be the first to reach its energy peak in 2027. Dynamic scenario simulation shows that the building sector will peak at 3.09 (±0.36) Bt CO 2 in 2037 (±4). Specifically, the urban residential building sector will peak at 1.27 (±0.18) Bt CO 2 in 2040 (±4), while the rural residential building sector will peak at 0.51 (±0.03) Bt CO 2 in 2021 (±4) and the commercial building sector will peak in 2038 (±4) at 1.41 (±0.30) Bt CO 2. Dynamic sensitivity analysis indicates that rural–urban migration will exert promoting effect on the peaking time and emission peaks of building carbon emissions through the concomitant effects of the urbanization process, i.e., the economic urbanization and space urbanization. Overall, this study can provide a better insight into the impact of urbanization on carbon emission peak and can support governments and decision-makers to formulate effective carbon-mitigation strategies. [ABSTRACT FROM AUTHOR]