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Abstract With the surging urbanization process and rapid economic growth in the service industry, carbon emissions released by the commercial building sector have become critical for China's national action towards meeting the "Post Paris" mitigation target. This paper is the first to confirm whether carbon intensity in the commercial building sector decouples from the economic development in service industry via the decomposition and decoupling methods at both the scales of the nation and the top five urban agglomerations [Jing-Jin-Ji (JJJ), Yangtze-River-Delta (YRD), Pearl-River-Delta (PRD), Yangtze-River-Middle-Reach (YRMR), and Cheng-Yu (CY) urban agglomerations] in China during the 2000–2015 period. The key findings indicate the following. The nationwide decoupling status was weak from 2001 to 2005 and then strong from 2006 to 2015. At the scale of urban agglomeration, only four states were observed in the decoupling status, and the order of the decoupling statuses across the different urban agglomerations is as follows: JJJ > CY > YRD > PRD > YRMR (2001–2005), YRD > JJJ > PRD > CY > YRMR (2006–2010), and YRD > YRMR > JJJ > CY > PRD (2011–2015). The carbon Kuznets curves of the commercial building sector successfully reveal the causes of the different decoupling paths across different urban agglomerations. The growing decoupling effects can be attributed to the rapid development of energy conservation projects in the commercial building sector over the past decade. Overall, it is expected that our contribution covers the research gap of decoupling carbon intensity in the commercial building sector from economic growth in the service industry, and our efforts constitute a significant contribution to the analysis of the carbon emission peak in the Chinese commercial building sector. Graphical abstract Decoupling elasticities of carbon intensity in the China's commercial building sector at the scales of the nation and urban agglomerations from 2001 to 2015. Image 1000 Highlights • Presenting the decoupling analysis integrating decomposition and decoupling methods. • Decoupling analysis of commercial buildings and the service industry was performed. • The case areas were China's top five urban agglomerations during the 2000–2015 period. • The decoupling levels of the five urban agglomerations were ranked and analyzed. • A pathway to achieve more significant decoupling effects was discussed and proposed. [ABSTRACT FROM AUTHOR]

Scientific assessment of the historical carbon peak situation of provincial buildings in China is the premise and basis for understanding the country's development trends and formulating carbon peak goals. The population size, urbanization stages, economic development levels, natural resources endowment, and energy structure characteristics vary significantly for the different provinces in China, resulting in significant differences in the peaking situation of building carbon emissions (BCE). The differences require more attention given the current environmental status. Based on the judgment function of carbon peaking conditions and the statistical Mann-Kendall (MK) trend test method, this study evaluates the historical peak situation of building carbon emissions at the provincial level in China. The peaking sequence of BCE, building carbon emissions per capita (BCEP), and carbon emissions per unit floor area (BCEA) were analyzed, and the driving factors that cause different carbon peak situations were discussed. Further, with reference to the experience of the United States, a peak strategy for building carbon emissions in China was proposed. The research results showed that BCE in Beijing and Yunnan have peaked, and the three provinces of Shanghai, Sichuan, and Hubei have plateaued. The most important factors that cause different peaking situations for BCE are the floor area per capita and carbon emissions per unit of energy consumption. In addition, the peak order of building carbon emissions was BCEA, BCEP, and BCE. A strategy that should be adopted in the promotion of buildings' carbon peak in China is to formulate phased peak goals for BCE, BCEP, and BCEA at a national level and differentiated echelon peak goals at a provincial level considering interprovincial differences. This study provides a scientific basis and decision-making reference for formulating a path to buildings' carbon peak at a provincial level in China. [Display omitted] • An assessment method for the peak situation of building carbon emissions is constructed. • Beijing, Yunnan have peaked, and Shanghai, Sichuan, Hubei have plateaued. • Carbon emissions per floor area reaches the peak earlier than building carbon emissions. • Carbon emissions per unit of energy consumption determines the different peak situations. • Peak strategy needs to be formulated at both national and provincial levels. [ABSTRACT FROM AUTHOR]

Revealing the long-term development trajectory and peak scenarios of the urban residential building sector is crucial for formulating targeted emission reduction strategies and contributing to achieving the "Dual carbon" target. Given that, significant variables affecting carbon emissions from urban residential buildings (URBCE) at both macro and end-use building levels are identified in this study. Furthermore, an innovative dynamic simulation model is developed by integrating the Monte Carlo simulation model with the Kaya identity model, taking into account the uncertainties of the variables. Subsequently, the long-term evolution trajectories, potential emission peaks, and peak time of the URBCE close to 2060 in China's hot summer and cold winter (HSCW) zone are simulated. Results indicate that URBCE is expected to reach its peak of 272.43 Mt CO 2 in 2040 under the baseline scenario. Through the dynamic simulation, the probable peak time of energy consumption in the HSCW zone is 2044 (±1.85), with a peak of 145.42 (±6.91) Mtce, and the possible peak time of carbon emissions is probably 2039 (±1.60), with a peak of 271.93 (±13.40) Mt CO 2. According to dynamic sensitivity analysis, carbon emission factor, per capita residential space, and heating energy intensity can promote the peak size and timing. These findings lay a robust foundation for the formulation of regionally specific carbon reduction targets and initiatives. Dynamic simulation results of peaking time and peak value of URBEC and URBCE. [Display omitted] [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]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [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]

Under global warming and severe environmental problems, the Paris Agreement urges China to accelerate the pace of the low-carbon economy. Improving the energy efficiency of the construction sector may be an important way to reduce CO 2 emissions. As a reasonable energy policy instrument, a carbon tax can effectively improve energy efficiency and reduce CO 2 emissions. In this study, a dynamic computable general equilibrium model is developed to explore the possible impacts of different carbon tax conditions on the energy consumption of the construction sector and the macroeconomy of China. Results show that the appropriate carbon tax is 60 RMB/t, which cannot only achieve the emission reduction target but also minimize the negative impact on the macroeconomy. However, the proper level of the carbon tax varies by building stage. Under the proper carbon tax level, the peak of carbon emissions could be reached in 2025. The main purpose of this paper is to provide a theoretical basis for the government in formulating different energy policies. • A computable general equilibrium model is established to explore the proper carbon tax for the construction sector. • The appropriate carbon tax rate for the construction sector is approximately 60 RMB/t. • Total amount of carbon emissions from the construction sector will peak by 2025 at the appropriate carbon tax level. [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]

(a–f) Changes of carbon reductions of commercial building operations at the provincial level and (g) the difference with the nation-based results (2001–2016). [Display omitted] • Provincial carbon intensity of commercial building operations grew 2.88 % yr−1 in 2001–2016. • Northeast and north China mitigated the most in carbon intensity and emissions, respectively. • Southwest China showed the highest ratio of carbon reductions to carbon emissions at 29.53%. • The total reduction of China's commercial building operation was 1.38 GtCO 2 in 2001–2016. • Annual provincial reductions peaked in 2013, one year earlier than the national result. The growing energy consumption in commercial building operations has slowed the pace of carbon reduction in the building sector, which has hindered China's movement towards peaking emissions by 2030 and carbon neutrality by mid-century. Considering the technical, socio-economic, climatic, and behavioral factors, this study evaluates the carbon reduction changes of commercial building operations in China's 30 provinces during the period 2001–2016. An assessment framework of the reduction intensity, amount, and efficiency has been built by carbon intensity decomposition. It shows that (1) the average provincial carbon intensity of commercial building operations kept rising by 2.88% per year from 2000 to 2016; (2) provinces of northeast and north China, respectively, took the lead in reduction intensity and amount at 17.09 kg of carbon dioxide per square meter and 73.79 megatonnes of carbon dioxide (MtCO 2) from 2001 to 2016. Meanwhile, the greatest efficiency of carbon reduction was seen in provinces of southwest China with the highest reductions-emissions ratio being 29.53%; (3) compared to the national level results, the annual carbon reductions based on provincial units hit their peak one year earlier at 167.35 MtCO 2 in 2013, although similar emission drivers have been observed. Moreover, effective practices by local governments have been summarized for energy efficiency promotion in commercial building operations. Overall, this study makes a reference for other economies to assess the historical carbon reduction in the building operation, which provides policymakers with insights into balanced and targeted emission reduction strategies towards a low-carbon transition in commercial building sector. [ABSTRACT FROM AUTHOR]

(a) Historical carbon emission mitigation of the residential building sector and (b) emission benchmarks of the future residential building sector in China. • Carbon mitigation of the residential building sector in 2000–2015 is 1.817 (±0.643) BtCO 2. • Residential building will achieve its emission peak in 2037 (±4) at 1.419 (±0.081) BtCO 2. • Floor space per capita and energy intensity are determining in the uncertainty of emission peak. • Future residential building energy benchmark should be controlled at 0.703 (±0.042) Btce. • A benchmark of 1.258 BtCO 2 can achieve the residential buildings' 2030 emission peak goal. Fast-growing carbon emissions from the residential building sector are a hindrance for China to achieve its 2030 emission peak goal. To identify future low carbon roadmaps of residential buildings, this study is the first to assess the historical carbon mitigation and simulate the energy and emission peaks of China's residential building sector using a dynamic emission scenario. It shows that the emission mitigation of the residential building sector during 2000–2015 is 1.817 (±0.643) billion tons of carbon dioxide (BtCO 2), and the normal distribution-based scenario simulation demonstrates that the residential building sector will achieve its carbon emission peak in 2037 (±4) with a peak value of 1.419 (±0.081) BtCO 2. The sensitivity analysis reveals that the impacts of floor space per capita and energy intensity of urban residential buildings are the most significant for the uncertainty of emission peaks. A strict energy demand benchmark of the residential building sector suggests a control at 0.661 billion tons of standard coal equivalent (Btce), and its peaking time is estimated for 2035, which is 5 years ahead of the business-as-usual scenario, with energy savings of 0.042 Btce. For the earliest peaking time, if the residential building sector aims to achieve its emission peak before 2030, the emission peak should be controlled at 1.258 BtCO 2. Overall, this paper can assist the government in more accurate and feasible building emission mitigation strategies. Moreover, the results provide a more powerful decision-making reference in issuing targeted and feasible strategies for future residential building emission mitigation. [ABSTRACT FROM AUTHOR]