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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]

[Display omitted] • Establishes an integrated dynamic emission assessment model by coupling end-use energy model and system dynamics model. • Explores the dynamic interaction mechanism between macrolevel and microlevel factors as well as technical options. • Commercial buildings will probably hit the emission peak at 1.28Gt CO 2 in 2037 under the BAU scenario. • Lighting and cooling will contribute over 70% to the carbon emission growth. • Technological progress, clean energy, and electrification rate play significant roles in boosting emission peak and peaking time. Carbon-mitigation in the commercial building sector is critical to carbon peaking and carbon neutral commitment. However, there has been little scientific focus on long-term evolutionary trajectories and peak path in this sector. This study innovatively develops an integrated dynamic emission assessment model (IDEAM) by combining the system dynamics model with the bottom-up end-use energy model. Moreover, the IDEAM is combined with the scenario analysis approach to model the dynamic evolution of Chinese commercial building carbon emissions toward 2060. The results show that commercial building carbon emissions will peak at 1.28 Gigatons (Gt) of CO 2 in 2037 under the baseline scenario and will advance toward 2029 with an emissions peak of 0.98 Gt CO 2 under the low-carbon scenario. Cooling and lighting are the two end-uses that contribute most to the growth of carbon emissions at over 70%. These two end-uses indicate different carbon-abatement potentials across climate zones. Sensitivity analysis reveals that promoting technological progress, increasing the share of clean energy, and improving low-carbon awareness are major ways to facilitate the early realization of carbon peaks and carbon neutrality. This study provides a deeper understanding of possible emission pathways and could assist policy-makers in devising scientific carbon mitigation plans. [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]

(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]

Residential central heating (RCH) is an important part of residents' well-being policy. However, it is accompanied by extensive energy consumption and carbon emissions. To identify and design efficient future clean heating strategies, we quantified the carbon emissions from RCH in China from 2000 to 2017. Notably, our study is the first to analyze the driving factors of RCH carbon emissions using decomposition analysis and introduce the climate parameter into the Kaya identity. The following results were obtained. 1) The RCH carbon emissions reached the flection point in 2016 (321.75 MtCO 2). 2) Area-related energy intensity is the key driving factor to mitigate carbon emissions of RCH; the area-related carbon intensity in 2017 was one-third less than that in 2000. Conversely, per capita residential heating area and urban population increased carbon emissions from RCH. 3) At the provincial level, the recommended emission mitigation strategies were different. For example, Heilongjiang and Jilin should focus on decreasing the emission factors, whereas Shandong and Xinjiang need to focus on decreasing the area-related energy intensity. The results of this study can help governments to formulate more rational and feasible policies for the emission road map, and the targeted advice also offers a reference for future studies. [ABSTRACT FROM AUTHOR]