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In this paper, a novel experimental investigation was conducted to enhance the combustion of boron-containing fuel-rich mixture by steam reforming in a supersonic flow. The ground direct-connected experiments were designed to simulate a flight condition at Mach number 5.9 and an altitude of 25 km. The operating characteristics and performance evaluation of the scramjet combustor were analyzed and discussed. The experimental results demonstrate that steam reforming can enhance the combustion of boron-containing fuel-rich mixtures in the supersonic flow. The performance of the combustor is firstly enhanced and then weakened with the increase of the steam-fuel ratio. The optimal steam-fuel ratio is approximately 0.189, which maximizes performance. At this steam-fuel ratio, combustion efficiency reaches 0.451, which is 9.9 % and 7.4 % higher than steam-fuel ratios of 0 and 0.395, respectively. The possible mechanism of steam reforming promoting boron combustion in the supersonic mainstream is explained. Steam accelerates the removal of the liquid oxide layer surrounding the boron particle, then combines with oxygen to produce hydrogen with good ignition-combustion characteristics and a new oxide layer. The cycle continues until the boron burns out. These conclusions can promote an understanding of enhancing the combustion of boron-containing fuel-rich mixture by steam reforming in the supersonic flow. [ABSTRACT FROM AUTHOR]

• Concentrations of Na and K in a MSW incinerator were measured. • Effect of combustion stage of MSW on concentrations of Na and K was analyzed. • Correlation between flame temperature and concentrations of Na and K was studied. • The concentration of Na and K was positively correlated with the primary air flow. To comprehensively understand the release characteristics of alkali metals which can cause corrosion and slagging problems in municipal solid waste (MSW) incinerators, the temporal concentrations of sodium (Na) and potassium (K) in a 16 MW MSW incinerator were measured employing a calibrated flame emission spectroscopy (FES) system. The experimental results revealed that the concentrations of alkali metals increased first and then decreased from the left side to the right side of the MSW incinerator. The maximum concentrations of Na and K were 111 ppm and 184 ppm, respectively. The peak and average concentrations of K near the left wall were 27 % and 58 % higher than those near the right wall at the same height of the MSW incinerator, owing to the different combustion stages of the MSW. The differences of the peak and average concentrations of K at the different heights of the MSW incinerator were 33.7 % and 23.5 %, respectively. Moreover, a positive correlation between the concentration of alkali metals and flame temperature was confirmed during the char phase combustion stage. Since the primary air distribution pattern of MSW incinerator decreased form the left side to the right side, the concentration of alkali metals near the left wall was positively correlated with the primary air flow, and that near the right wall exhibited a positive correlation with the garbage caloric value. This research provided an effectual solution for in-situ measurement of alkali metal concentration and flame temperature in MSW incinerators. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) caused by residential building sector is essential for China to achieve its 2030 carbon emission peak. As the indicator to control the total CO 2 emissions, CO 2 intensity feature should be preferentially analyzed. Through the decomposition and decoupling approaches, this paper is the first to investigate whether CO 2 intensity decouples from the income level in residential building sector of China and its four megacities [Beijing (BJ), Tianjin (TJ), Shanghai (SH), and Chongqing (CQ)] from 2000 to 2016. Major findings indicate that: (1) The nationwide status was the weak decoupling during 2001–2016 excluding 2003 (the expansive coupling) and 2014 (the strong decoupling). (2) At the megacity scale, only four decoupling levels appeared and the decoupling effect rank of four megacities is as follows: CQ > TJ > BJ > SH (2001–2004), BJ > TJ > CQ > SH (2005–2008), SH > BJ > TJ > CQ (2009–2012), and SH > BJ > TJ > CQ (2013–2016). (3) Carbon Kuznets curves explained the different decoupling modes of four megacities and the increasing decoupling effects in 2001–2016 are attributable to the implementation of energy conservation strategy. Overall, this paper fills the gap of decoupling CO 2 intensity from the income level in residential building sector. Furthermore, a significant contribution is made by this paper to the carbon emission peak analysis in residential building sector of China, and our efforts will also be a case for other countries and cities to evaluate the decoupling effect in their residential building sectors. Decomposition and decoupling results of CO 2 intensity in residential building sector of China and its four megacities (2000–2016). Unlabelled Image • Proposing the comprehensive analysis via decomposition and decoupling approaches • Decoupling CO 2 intensity from the per capita income was implemented. • Case areas focused on residential buildings of China and its four megacities. • Energy conservation strategy of China's residential buildings was reviewed. • Approaches on realizing more significant decoupling effects were discussed. [ABSTRACT FROM AUTHOR]

Abstract China has launched the energy efficiency project (EEP) for its civil building sector beginning in the mid-1980s; however, its implementation has not been effective. To better promote the EEP for the Chinese civil building sector, the Chinese government issued the China Act on the Energy Efficiency of Civil Buildings in 2008. This is the first paper to present a review of this act's implementation over the past decade. Based on China Database of Building Energy Consumption and Carbon Emissions and official documents, the achievements of this act are assessed by examining a variety of indicators. The success of the act can be attributed to the following factors: 1) a strong and sustained government commitment to top policies of building energy efficiency (BEE); 2) extensive efforts to apply the BEE standards to newly built civil buildings; 3) various incentive schemes involving energy efficiency retrofitting for existing civil buildings; 4) the increasing adoption of renewable energy to the civil building sector and of systems and platforms of energy efficiency supervision to commercial buildings; and 5) the rapid development of green buildings. Nevertheless, the revised act must address several challenges in the upcoming phase. These challenges mainly include the following: 1) the "double-control" strategy for the civil building sector; 2) the substantial development of the EEP in rural China; 3) the further development of green buildings for the low-carbon civil buildings; 4) the improvement of official statistical data systems on energy consumption and carbon emissions for civil buildings; and 5) building industrialization and informatization. It's expected that our efforts as constituting significant guidance for evaluating the EEP in the Chinese civil building sector, and the efforts will also be treated as an example for other developing countries to evaluate and revise their BEE acts. Graphical abstract Energy-saving value assessment of the Chinese civil building sector based on an IPAT-LMDI approach. Unlabelled Image Highlights • Presented a decennial review of the act for the first time. • Proposed a decadal retrospection of building energy efficiency project in China. • Building energy savings in 2011–2015: 183 million tons of standard coal equivalent. • Means of revising the act were proposed. [ABSTRACT FROM AUTHOR]

Abstract Decoupling economic development from carbon emissions generated from China's commercial buildings (CECCB) is regarded as an important indicator for evaluating the energy efficiency of the commercial building sector in China. Our study is the first to propose a decoupling method based on a Logarithmic Mean Divisia Index (LMDI) decomposition analysis with the Kaya identity to analyze the relationship between economic development in China's Tertiary Industry and the CECCB growth at both national and municipal levels. The following three main results are found. (1) At the national level, commercial building sector decoupling from 2001 to 2015 is limited. Only four decoupling stages are observed at the municipal level with the ordering of municipal decoupling measured as follows: Tianjin > Beijing > Shanghai > Chongqing (2001−2010), Chongqing > Beijing > Tianjin > Shanghai (2011–2015). (2) Two extended versions of Environmental Kuznets Curves further show what drives different decoupling levels in the four municipalities. (3) More significant decoupling effects observed in recent years can be attributed to significant improvements made in the energy efficiency work of China's commercial building sector. Overall, our approach successfully covers a research gap relevant to the decoupling of the relationship between CECCB growth and the economic development of China's Tertiary Industry. Furthermore, we believe our results can be used to guide the evaluation of energy efficiency work in China's commercial building sector, and such efforts can also enrich diverse research conducted on China's low carbon economic systems. Graphical abstract Decoupling elasticity values in China's commercial building sector at both national and municipal levels for 2000–2015. Unlabelled Image Highlights • A decoupling analysis using Kaya and Logarithmic Mean Divisia Index methods is proposed. • The ordering of decoupling levels for 2001–2010 is Tianjin > Beijing > Shanghai > Chongqing. • The ordering of decoupling levels for 2011–2015 is Chongqing > Beijing > Tianjin > Shanghai. • More significant decoupling effects can be achieved by enhancing levels of energy efficiency. [ABSTRACT FROM AUTHOR]

Abstract 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. Graphical abstract The building stock in China's different provinces and climate zones in 2015. Image Highlights • Proposed a China building floor space estimation method (CBFSM) based on improved building stock turnover model. • Estimated China's building stocks by type and vintage from 2000 to 2015 using CBFSM. • Calculated the building energy intensity at the national level and provincial level. • Estimated the size of the energy efficient buildings in China. • Validated the results of study by comparing with the data from China Population Census; the deviations are well below 10%. [ABSTRACT FROM AUTHOR]

Abstract Measuring carbon abatement in China's commercial buildings (CACCB) has been recognized as a path to evaluate the energy conservation work (ECW) in China's commercial building sector. This study first presents a bottom-up model for measuring the CACCB values based on decomposing the extended Kaya identity via the Logarithmic Mean Divisia Index (LMDI) method. The results indicate that (1) mainly three types of drivers (f , d , and K) contributed negatively to the carbon intensity of commercial buildings from 2000 to 2015, and the comprehensive effects were quantified as the intensity values of CACCB. The CACCB values in the three Five-Year Plan periods were 383.41 (2001–2005), 591.09 (2006–2010), and 621.54 MtCO 2 (2011–2015). (2) A comparative analysis of the contribution rate elasticity of the drivers assessed by the LMDI method and ridge regression effectively examined the robustness of the CACCB measurement model. Meanwhile, the performance of the measurement model was also evaluated. (3) More significant CACCB effects observed in recent years can be attributed to significant improvements made in ECW. To sum up, we believe that our approach covers the research gap of CACCB measurement, and our efforts constitute significant guidance for developing future ECW in China's commercial building sector. Graphical abstract Image Highlights • Carbon abatement in China's commercial buildings (CACCB) in 2001–2015: 1596.04 MtCO 2. • Developed a bottom-up measurement model for CACCB based on the Kaya-LMDI methods. • Proposed a robustness analysis for the measurement model based on the ridge regression. • Conducted a decadal overview for energy conservation work in the commercial building sector. • A pathway to achieving more significant carbon abatement was discussed and proposed. [ABSTRACT FROM AUTHOR]

Energy efficiency in the building sector is expected to contribute >50% to the nationwide carbon mitigation efforts for achieving China's carbon emission peak in 2030, and carbon mitigation in Chinese commercial buildings (CMCCB) is an indicator of this effort. However, the CMCCB assessment has faced the challenge of ineffective and inadequate approaches; therefore, we have followed a different approach. Using the China Database of Building Energy Consumption and Carbon Emissions as our data source, our study is the first to employ the Logarithmic Mean Divisia Index (LMDI) to decompose five driving forces from the Kaya identity of Chinese commercial building carbon emissions (CCBCE) to assess the CMCCB values in 2001–2015. The results of our study indicated that: (1) Only two driving forces (i.e., the reciprocal of GDP per capita of Tertiary Industry in China and the CCBCE intensity) contributed negatively re m i to CCBCE during 2001–2015, and the quantified negative contributions denoted the CMCCB values. Specifically, the CMCCB values in 2001–2005, 2006–2010, and 2011–2015 were 123.96, 252.83, and 249.07 MtCO 2 , respectively. (2) The data quality control involving the CMCCB values proved the reliability of our CMCCB assessment model, and the universal applicability of this model was also confirmed. (3) The substantial achievements of the energy efficiency project in the Chinese commercial building sector were the root cause of the rapidly growing CMCCB. Overall, we believe that our model successfully bridges the research gap of the nationwide CMCCB assessment and that the proposed model is also suitable either at the provincial level or in different building climate zones in China. Meanwhile, a global-level assessment of the carbon mitigation in the commercial building sector is feasible through applying our model. Furthermore, we consider our contribution as constituting significant guidance for developing the building energy efficiency strategy in China in the upcoming phase. [ABSTRACT FROM AUTHOR]

• A new method was proposed to measure flame temperature in RBCC combustion chamber. • Effects of equivalence ratio on flame temperature were investigated. • The position of peak flame temperature oscillated with time sequence. • Effects of laser-induced plasma and plasma jet torch on combustion were analyzed. The extremely harsh environment and highly unsteady and transient nature during supersonic combustion bring great challenges for quantitative diagnostics. In the present work, for the first time, we report measurements of two-dimensional distributions of flame temperatures in a Rocket-Based Combined Cycle (RBCC) combustion chamber using a multispectral imaging technique with both spatial and spectral resolutions. The relation between the multispectral radiation intensity images and the flame 2-D temperature distributions was established by combing the Lvevenberg-Marquardt algorithm and the Hottel and Broughton emissivity models. The experimental results revealed that both laser-induced plasma (LIP) and plasma jet (PJ) torches had positive effects on combustion stabilization, and LIP had better effect on combustion enhancement. In the ignition stage of a fuel/air mixture with an equivalence ratio of 1.0, the average temperature of a flame initiated by LIP combustion enhancement was 100 K higher than that by PJ torch combustion enhancement. A recirculation zone was formed inside a cavity, which improved the combustion stability. The injected fuel and inflow were most fully mixed on the slope at the rear of the cavity, where 70 % and 65 % of the peak flame temperature points of LIP and JP were located, respectively. The combustion in the RBCC chamber showed an oscillation phenomenon that peak flame temperature and the flame structure oscillated continuously around the central axis with a horizontal extent of 162 mm. Due to the insufficient fuel blending, the oscillation amplitude was minimal when the equivalence ratio was 1.0. Overall, the results of flame temperature distributions demonstrated that the proposed multispectral thermometry was suitable for measuring temperatures of supersonic combustion flames. [ABSTRACT FROM AUTHOR]

• A new method was proposed to measure MSW flame temperature and emissivity. • Effects of MSW composition on flame temperature and emissivity were analyzed. • The characteristic spectral of Na and K in MSW combustion were measured. • The radiative properties of MSW flames changed with the feeding MSW species. By using a novel multispectral imaging technology, the 2-D distributions of flame temperature and emissivity were measured in a 16 MW incinerator to co-fire municipal solid waste (MSW) and municipal sludge. A way to establish the relationship between the multispectral flame images and the temperature was proposed by combing the Newton iteration method and Hottel emissivity model. The results showed that the measured temperatures at different locations varied by 31.25% with a fixed steam evaporation rate, and 11.76% with different steam evaporation rates at a given port. The temperatures and emissivities decreased at upper locations due to the lower local soot particle concentration and the change of the measured flame temperatures with load were correlated with the MSW caloric values. Flame temperatures near the left wall were higher than those near the right wall. This deviation was caused by the high moisture content of municipal sludge that inhibited combustion. The emissivities of flame near the right wall were lower than those near the left wall due to the low fixed carbon in municipal sludge. The normalized flame emissivities between the left and the right walls indicated that obvious differences existed in the radiative characteristics of soot, which confirmed the uneven mixing of MSW and municipal sludge. Besides, a spectrometer system was used to measure the release of alkali metal elements including Na, K during the incineration process. The characteristic spectra showed that the alkali metal radiative intensity was related to the moisture content in the wastes. Overall, these results justified that the multi-wavelength thermometry was feasible for monitoring combustion in the MSW incinerator. [ABSTRACT FROM AUTHOR]

The construction industry plays a crucial role in achieving carbon neutrality by reducing energy consumption. However, Building energy consumption (BEC) in China is increasing concomitantly with the rapid increase in urbanization. This study utilizes nighttime light data to construct a nighttime light index for urbanization, and empirically studies the impacts of urbanization on BEC intensity. The results show that there is a statistically significant positive correlation between BEC intensity and urbanization level on a nationwide scale, while an inverted-U relationship exists in Eastern developed regions, suggesting that an increasing BEC intensity is not an inevitable result of urbanization. Urbanization in the compact city mode inhibits BEC intensity to some extent, while urbanization in the urban sprawl mode often develops at the expense of increasing BEC intensity. The acceleration of the regional coordinated development and the adoption of the compact city mode are suggested to achieve energy-saving and emission-reduction targets. [ABSTRACT FROM AUTHOR]

• Multispectral imaging technique was used to measure flame radiation intensity. • A new method was proposed to reconstruct candle flame temperature and emissivity. • Candle flame combustion characteristics with different materials were analyzed. • The characteristic spectral intensities of K were measured. Due to the low spatial resolution of spectrometer and low spectral resolution of CCD, a multi-wavelength radiation thermometry method employing multispectral imaging technology was proposed to measure flame temperature and emissivity. The calculated radiation intensity lines were obtained by the Hottel emissivity model and the least square method. The temperature and flame absorption capacity with the calculated spectral line closest to the measured spectral line were considered as the optimum results. The experimental results showed that maximum temperature of the flame was 1943 K appeared in the thin-wick paraffin. At any position, the emissivity of the thin-wick paraffin flame was lower than that of the thick-wick, but the emissivity of the biomass candle flame near the flame center was the highest. The measured temperature distribution was validated by employing a spectrometer system and the relative error was 2.66%. [ABSTRACT FROM AUTHOR]

• Carbon emissions and human development were coupled for sustainability. • Approaches on exploring the coupling effect were proposed for the first time. • Data on China's provincial-level human development index were detailed. • Coupling status was discussed via the clustering quadrant method. Lessening energy-related carbon emissions has become a crucial measure to achieve Chinese carbon neutrality. This study is the first to construct a Difference in Carbon pressures-adjusted Human Development Index (DCHDI) model for the purpose of exploring the coupling effect between carbon emissions and human development variety from 2000 to 2019 in Chinese provinces. We demonstrate the following. (1) The total energy-related carbon footprint of 30 provinces in China reached 10.2 billion tons in 2019, with an average annual growth rate of 6.93% over the past two decades; and the provinces with the highest carbon emissions per capita are InnerMongolia, Ningxia, and Shanxi. (2) At the provincial level, we observed that the Human Development Index (HDI), which includes life expectancy, education, and income, has been rising, while Beijing, Shanghai, and Tianjin entered the super-high HDI level before 2008. (3) The entire coupling effect of 30 Chinese provinces has been broadly fortified in the last 20 years, but the growth rate of DCHDI values in 2011–2019 has slowed down compared with that in 2000–2010; the clustering phenomenon demonstrated that this discovery is associated with historical peaks in total carbon emissions. (4) The coordination degree of carbon emissions per capita and HDI was verified, and 96% of the data points were found in the range of super high coupling coordination degree. Overall, this study provides the government with worthwhile guidance for decision-making and carbon reduction strategies for other countries struggling to advance human sustainable development. [ABSTRACT FROM AUTHOR]

Reducing energy-related carbon emissions has become the essential measure to mitigate global climate change. Based on decoupling analyses and index decomposition, this study is the first to explore whether carbon emission per capita decouples from the human development index from 2000 to 2015 at the provincial level in Southwest China [Chongqing (CQ), Sichuan (SC), Guizhou (GZ), and Yunnan (YN)]. We demonstrate the following. (1) The economic output and energy intensity effects among the five drivers are the strongest to promote and suppress the growth of carbon emission per capita from 2001 to 2015. (2) At the provincial level, we observed four decoupling statures, and the decoupling impact was organized in decreasing order: CQ > GZ > SC > YN (2001–2005), GZ > YN > CQ > SC (2006–2010), YN > SC > GZ > CQ (2011–2015). (3) The overall decoupling effect of Southwest China has been generally reinforced from 2000 to 2015, and finally entered a strong decoupling status in 2013–2015; an environmental Kuznets curve explained that this finding is related to historical peaks in total carbon emissions. Overall, this study provides guidance for the government on carbon emissions mitigation strategies and a valuable decision-making reference for other regions attempting to accelerate low-carbon development. Decomposition and decoupling results of carbon emission per capita at the provincial scale in Southwest China in 2000–2015. Unlabelled Image • Decoupling carbon emission per capita from the human development index in 2000–2015; • Applying the decoupling model through index decomposition and Tapio index analyses; • Total carbon emissions focused on 17 fossil fuels and 47 socioeconomic sectors; • Approaches to enhancing the higher decoupling effect were discussed. [ABSTRACT FROM AUTHOR]

Electrification is important for carbon reduction in urban residential buildings. It requires clean regional grids to achieve positive emissions efficiency. In countries where the condition of regional grid decarbonization varies, such as China, an aggressive electrification strategy may increase carbon emissions. However, existing research lacks attention to coordinating building electrification with regional grid decarbonization. This study projects the regional timetable when replacing fuel appliances with electric appliances can reduce carbon emissions from 2022 to 2050. Four strategies with different schedules are designed, of which the carbon emissions are compared under three grid decarbonization scenarios. Results find the following: First, in most regions, replacing gas appliances with high-efficiency electric ones can already reduce carbon emissions, while the transition to direct electric-to-heat appliances takes a long time. Secondly, the current national simultaneous strategy will increase carbon emissions by at least 52MtCO2 when using direct electric-to-heat appliances. The increments come from the Northeast, North, and East. Thirdly, high-efficiency electric appliances can reduce the sensitivity of the emission reduction potential of electrification strategies to the onset time. The study contributes to decision-making processes related to electrification strategies for urban residential buildings, providing a reference for assessing their potential to reduce emissions. • Most regions will take long to reach the carbon emission factor for electric-to-heat appliances to replace gas ones. • Electrification strategies may either reduce or increase carbon emissions. • To prevent carbon lock-in or early retirement of fuel appliances, electrification could be incentivized earlier. • Electrification strategies face many challenges. It is recommended to conduct pilot projects before initiating action. [ABSTRACT FROM AUTHOR]

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]

Abstract Accurate estimation of urban residential building-related energy consumption (URBEC) and energy intensity per unit floor area at the national level has significant implications for the analysis of carbon emission peaks. However, reliable data on China's building floor space (BFS) are lacking, resulting in unclear energy intensity levels. This study proposes a China BFS estimation method (CBFSEM) based on improved building stock turnover model. Using CBFSEM, it estimates the BFS of historic urban dwelling stock, the demolished and newly built dwelling from 2000 to 2015. It then estimates the corresponding energy consumption and intensity based on the obtained urban residential BFS data. Results showed that total URBEC in China increased dramatically from 217.1 Mtce in 2000 to 417.2 Mtce in 2015 with an average annual growth rate of 4.45%. China's total dwelling stock almost doubled, from 10.6 billion m2 in 2000 to 27.4 billion m2 in 2015 with an annual growth rate of 6.56%. The operational energy consumption accounted for approximately 70% of total URBEC and the building material production energy intensity was the highest in total URBEC, >60 kgce/m2. A comparison with the China Population Census showed that the deviations were well below 8%, which indicated the reliability of the CBFSEM and the estimated results. In general, this study fills the gap in available data and addresses the shortage of estimation methods for BFS and energy intensity. It also provides the government with technical support and scientific evidence to promote building energy efficiency. Graphical abstract Unlabelled Image Highlights • Proposed an urban residential building-related energy consumption (URBEC) and energy intensity estimation framework • Proposed a China building floor space estimation method (CBFSEM) • Estimated China's dwelling stocks, demolished and newly built residential BFS from 2000 to 2015 • Estimated urban residential building-related energy consumption and intensity of the building sector • Validated the results of study by comparison; the deviations are well below 8% [ABSTRACT FROM AUTHOR]

Urban household Electricity Consumption (UHEC) is receiving more and more attention in terms of energy saving and emission reduction. Currently, China lacks a mature methodology to explore the impacts and mechanisms of UHEC. This study selects physical characteristics, usage, and equipment factors associated with urban domestic dwellings to address these issues to develop an adequate theoretical model. The extended STIRPAT model was used to explore how each factor affects UHEC. Stepwise regression was then used to identify the mechanisms of influence between each factor and UHEC and to investigate the direct and mediating effects between floor area and UHEC. The results show that floor area, urbanization rate, the proportion of older people, per capita income, and unit energy consumption significantly contribute to UHEC. The direct effect of floor area on UHEC reaches 13.5%. GDP per capita and urbanization rate have a strong mediating role, at 47.8% and 28.1%, respectively, and the mediating contribution of unit energy consumption is 11.8%. A more novel factor, namely single-person households, shows a significant masking effect. In summary, this study is cutting-edge and provides a scientific decision and basis for developing household electricity-saving strategies in China and the world. • The extended STIRPAT model examines the effects of multiple factors on UHEC. • Mediation effects were used to identify mechanisms of influence between factors. • Significant provincial UHEC differences drive energy mix optimization. • Single-person households are a special variable presenting a masking effect. • Policy subsidies may mitigate the impact of aging and singlism on UHEC. [ABSTRACT FROM AUTHOR]

The significant differences in the level of economic development, energy structure, and natural resource endowments between provinces in China means that the development trajectories of building carbon emissions also differ significantly. Therefore, conducting peaking studies of building carbon emissions only at the national level may lead to large errors. Using a combination of top-down and bottom-up approaches and considering the actual situation of each province, this study constructed a provincial-level building carbon emission model for China and established differentiated scenario parameters based on peak and time constraints. By comparing and analyzing the peak value and peak time under different scenarios, the effective echelon peaking path for provincial building carbon emissions was determined. The results show that the transitional regions with high urbanization rates such as Jiangsu and Zhejiang, and the eastern regions with economically developed such as Beijing, Tianjin, and Shanghai should take more responsibility for emission reduction, and reach the peak of building carbon emissions earlier. Instead, a certain time and space for development should be given to the central regions with relatively low urbanization rates and large populations such as Anhui, Henan, Hubei, and to the underdeveloped western regions such as Sichuan, Yunnan, Shannxi. This study provides a decision-making reference to achieve building energy conservation and emission reduction in Chinese provinces and foreign regions. [Display omitted] • Considering the national peak and time constraints, a provincial peak path was formulated. • China's building carbon emissions are expected to peak at 2.59 billion tCO 2 in 2030. • Regions with high urbanization rates and developed should peak first. • Regions with low urbanization rate, and large population can delay peaking. [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]

Heating in the Hot Summer and Cold Winter (HSCW) climate zone in China has become the fastest-growing part in urban residential energy consumption, with a high average annual growth rate of 50%. This creates opportunities for decision-makers to make effective policies on impacting energy consumer behavior. However, for these policy intervention strategies to be efficient and equitable, the factors determining heating energy usage need to be known. This study employs the quantile regression model to explore the heterogeneity in consumer response between groups by using survey data from 1075 households in 2016 in Chongqing, China. We identify the characteristics of high heating electricity-consuming households. Households with larger household sizes, more elderly family members, and high-income would tend to consume more electricity. In terms of building characteristics, more rooms and detached houses lead to higher heating electricity consumption. Additionally, higher-performance residential buildings can reduce household heating electricity consumption. Compared to central heating system, using split ACs and distributed electric heaters provide a smoother path towards increasing electricity load to achieve better thermal comfort. Our empirical findings have important regional policy implications to support heating policy design. Finally, strategies for reducing heating demand concerning high heating electricity-consuming households are provided. • Actual electricity data at household level are collected in a large-scale survey. • Quantile regression is used to analyze the heterogeneity in residential households. • The characteristics of high heating consumption households are identified. • Heating saving policy should focus on high heating-consuming households. [ABSTRACT FROM AUTHOR]

Cooling demand increases more than ten times over the past two decades in China. Especially, cooling in the Hot Summer and Cold Winter (HSCW) climate zone increases rapidly and becomes the fastest growing part in urban residential energy consumption. It will bring huge challenges to carbon emission cap control if effective and reasonable energy-saving and emission reduction measures are not taken. This study uses a data-driven method to identify cooling savings potential at household level using survey data from 1068 households in 2018 in Chongqing, China. A stochastic frontier analysis model is applied to decompose the actual cooling electricity consumption into minimum consumption based on fixed household characteristics and estimate the over-consumption (i.e. the amount of cooling consumption that could be saved). The results show that households have an average cooling efficiency of 65 %, which indicates that each household in the HSCW area has the potential to reduce its cooling electricity consumption by 35% while still maintaining the same level of cooling services currently produced. The study shows that the cooling savings potential is strongly influenced by level of household income, the level of building energy efficiency standards, cooling behavior characteristics and households' energy-saving consciousness. Policy implications are derived. • This paper provides a data-driven research paradigm for policy making. • A stochastic frontier approach is used to study the cooling savings potential. • There is a 35 % cooling savings potential via efficiency measures in the HSCW zone. • The key factors influencing the household cooling savings potential are identified. [ABSTRACT FROM AUTHOR]

To develop in-situ temperature measurement technology for biomass combustion environment, rose and tea soybean candle flames were experimentally studied using spectral thermometry in this paper. The distributions of temperature and emissivity at different flame heights were calculated using four emissivity models, i.e., the Gray emissivity model, the Hottel and Broughton emissivity model, the polynomial approximation emissivity model and the Rayleigh approximation emissivity model. The results showed that the emissivity calculated by the polynomial approximation emissivity model was larger than that calculated by other models at the same flame height. The average temperature of rose soybean candle flame was 59 K larger than that of tea soybean candle flame. The temperature results were verified by the hyper-spectral imaging device and the polynomial approximation emissivity model performed the best. Normalized emissivity showed that the radiative property of the rose soybean candle flame was stronger than that of the tea soybean candle flame. Moreover, the alkali metal content in the tea soybean candle flame was higher than that in the rose soybean candle flame along the flame height. [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 problem of household energy consumption (HEC) is gradually becoming prominent in the current situation of rough-style energy development. Household structure type plays a vital role in examining HEC heterogeneity. Based on data from the China Integrated Social Survey, this study examined the heterogeneity of household structure type and other factors on HEC through quantile regression. The conclusions show that the education level of household members, income, weekly working hours, days of residence, and home ownership contribute significantly to HEC. In contrast, the average age of the resident population is negatively associated with HEC. In addition, childless households and "spouse + parent" households have the lowest and highest effects on HEC, respectively, and a "neutralizing effect" occurs at the higher quartiles of HEC for three-generation households. There is heterogeneity in the impact of HEC among family members of different genders at the same age; the person with the primary consumers of HEC in the household is not always female, and males over 46 years of age replace females in the same age group as the primary consumers of HEC at the high HEC quartile, which is related to the age group. Finally, some policy recommendations were made. • Hours of work and days of residence per week are positively associated with HEC. • The effect of family type and number of members on HEC is small when HEC is large. • Neutralization effect occurs in three-generation families when HEC is large. • Spouse + parent type families have the most significant impact on HEC. • Males produce more HEC than females in certain age groups at high HEC quartiles. [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]

a. Changes of CO 2 emission per household (CO 2 intensity) in the Chinese residential building sector via decomposition analysis; b and c. Total and intensity values of CO 2 mitigation in the residential building sector (2001–2016); d and e. CO 2 mitigation per capita and CO 2 mitigation per floor space in the residential building sector (2001–2016). • Changes in CO 2 intensity were decomposed via the Log-Mean Divisia Index approach. • Average CO 2 mitigation intensity from 2001 to 2016 was 266.12 kgCO 2 ·(household·year)−1. • CO 2 mitigation of the residential building sector from 2001 to 2016 was 1816.99 MtCO 2. • Ridge regression verified the robustness of the CO 2 intensity decomposition results. • Energy-conservation and emission-mitigation strategy is the key to promoting CO 2 mitigation. Carbon-dioxide mitigation in residential building sector (CMRBS) has become critical for China in achieving its emission mitigation goal in the "Post Paris" period with the growing demand for household energy service in residential buildings. This is the first paper to investigate the factors that can mitigate carbon-dioxide (CO 2) intensity and further assess CMRBS in China based on a household scale via decomposition analysis. The core findings of this study reveal that: (1) Three types of housing economic indicators and the final emission factor significantly contributed to the decrease in CO 2 intensity in the residential building sector. In addition, the CMRBS from 2001 to 2016 was 1816.99 MtCO 2 , and the average mitigation intensity during this period was 266.12 kgCO 2 ·(household·year)−1. (2) Ridge regression indicated that the robustness of the decomposition approach was sufficient for achieving reliable results for the decomposition analysis and CMRBS assessment. (3) The energy-conservation and emission-mitigation strategy caused CMRBS to effectively increase and is the key to promoting a more significant emission mitigation in the future. Overall, this paper covers the CMRBS assessment gap in China, and the proposed assessment model can be regarded as a reference for other countries and cities for measuring the retrospective CO 2 mitigation effect in residential buildings. [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]

Space heating demand in the hot summer and cold winter (HSCW) climate zone in China has increased rapidly over the past decade. It poses significant challenges for China's electricity supply infrastructure and building decarbonization. This study aims to understand the relative energy efficiency of household space heating and identify potential opportunities to reduce electricity usage at the household level. A stochastic frontier analysis approach is used to quantify the energy efficiency of households' space heating by forming an efficient frontier (minimum requirement of consumption given the characteristics of the household) and by comparing all households against that frontier. The results indicate that the average household space heating efficiency is 0.69. This indicates that households in the HSCW area have the ability to reduce their heating electricity consumption by 31% while still keeping the current level of indoor thermal comfort in the winter. The level of building energy efficiency standards (BEES) is the key factor influencing the space heating savings potential. Thus, Policy choices should focus on revising and optimizing superior BEES, and accelerating energy efficiency retrofits of existing residential buildings in this region. • The space heating efficiency is calculated by the stochastic frontier approach. • Frontier space heating demand functions are estimated using household survey data. • The households have an average space heating efficiency of 0.69. • Building envelope performance is the key factor for household space heating efficiency. [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]

Long- or short-term exposure to air pollution would distort human's cognitive function which has aroused widespread concern in interdisciplinary fields. It furtherly seems rational to assume that air pollution may affect energy use in public buildings. However, the overlooks of the potential impacts of air pollution on energy use would result in substantially higher energy saving cost. By matching the real-time energy consumption of public buildings to indoor and outdoor PM 2.5 , we construct a panel containing 193,226 data items. Based on this, we conduct the first preliminary exploration to try to reveal the impact of PM 2.5 on energy use at the building-hourly level. Results show that the increase of energy intensity caused by PM 2.5 is subtle, it indeed exists significantly. When indoor PM 2.5 is 1 μ g / m 3 , the marginal effect is minimum. After indoor PM 2.5 exceeding 1 μ g / m 3 , the marginal effect began to increase and the maximum is 0.3224 when PM 2.5 is 1114 μ g / m 3. However, given the sorting and contrast effect, the practical relationship between indoor PM 2.5 and energy use is possible inverted-U shaped. Furtherly, we find long term exposure to outdoor PM 2.5 would not make people adapt to air pollution and instead cumulative the impact on energy use. Besides, centralized office could be an economical and feasible measure to achieve energy saving goal. Finally, we propose that it is promising for achieving the synergy between air pollution control and energy consumption reduction. • The relationship between indoor PM 2.5 and energy use is possible inverted-U shaped. • Long term exposure to outdoor PM 2.5 would not make people adapt to air pollution. • Centralized office is an economical and feasible measure to achieve energy saving. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Revealing the regional differences and drivers of provincial urban residential building sector carbon emissions (URBCE) is critical for regional collaborative emission reduction in achieving the "Dural carbon" targets. This study tries to innovatively construct a framework for the exploration of the spatiotemporal patterns and driving mechanism of Chinese URBCE in 30 provinces during 2000–2019, combining kernel density estimation, spatial autocorrelation analysis and temporal-spatial LMDI model. Results indicate that: (1) A vast majority of regions have undergone a sharp growth in URBCE, with the regional gap of URBCE gradually widening. (2) Besides, the spatial pattern of regional URBCE is basically stable, with High-High distributed in the Northeast and North China, and Low-Low concentrated in the Southwest. (3) Urban residential building floor space per capita, population, and urbanization are promotive driving forces, while carbon intensity and energy intensity are increasingly inhibiting. This study can provide policymakers a better understanding of URBCE and help them develop regionally-specific emission reduction strategies. Additionally, it offers fresh perspective on how to research the spatiotemporal disparities of carbon emissions in other sectors and nations, and could be of international significance. [Display omitted] • Establishes a framework to explore spatiotemporal patterns of provincial URBCE. • Investigates the spatial characteristics and dynamic evolution of regional URBCE. • Adopts temporal-spatial LMDI model to uncover the driving mechanism on URBCE. • A vast majority of regions have seen a sharp growth of URBCE during 2000–2019. • Floor space per capita, population, and urbanization are promotive drivers to the URBCE. [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]

National building energy savings (NBES) plays an essential role in policymaking of China's building energy–efficiency (BEE) work. Numerous factors, such as technological progress and users' behavior, affect NBES while most of them are unquantifiable. One missing possibility along this direction is that there is currently no method to calculate China's NBES by summarizing all driving factors. To arrive at a solution, we proposed a concept of comparable building energy consumption per unit area and a method of China's NBES calculation based on an extended version of IPAT model (I = PAT, I = Human Impact, P = Population, A = Affluence, T = Technology) and LMDI decomposition (Logarithmic Mean Divisia Index, LMDI). Calculation revealed that China's NBES in “The 10th Five–Year Plan” period (2001–2005), “The 11th Five–Year Plan” period (2006–2010), and the first four years of “The 12th Five–Year Plan” period (2011–2014) was 165, 158, and 127 million tce, respectively. Based on these calculation results, we checked NBES data then successfully proved the validity of this calculation method. Furthermore, after comparing the calculated NBES with the official planned NBES, we found that China surpassed its BEE targets. In the third stage of China's BEE work (2006–2015), the implementation of BEE policies obtained good results. [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]

Contributions of different end-use activities to carbon intensity changes in global commercial building operations in (a) 2000–2010 and (c) 2010–2019; (b) impacts of different end-use activities on decarbonizing the operational carbon intensity across different countries in 2000–2019. [Display omitted] • The carbon intensity of commercial building operations in 16 economies declined 1.9 % yr−1 in 2000–2019. • Emission factors and industrial structure were the key to decarbonizing the building operations. • Energy intensity (e.g., heating: −14.3 kgCO 2 /m2/yr) has pushed global decarbonization since the 2010 s. • Decarbonization level in 16 economies was 230.3 MtCO 2 /yr with a decarbonization efficiency of 10.1%; • Electricity decarbonization will be critical to achieving global carbon neutrality in commercial buildings. Building operations will be the most critical step in completing the "last mile" of global carbon neutrality. To seek the best practical path to decarbonize commercial building operations, this study assesses the decarbonization progress of commercial building operations in 16 countries over the last two decades considering socioeconomic, technical, climatic and end-use factors through the decomposing structural decomposition method. The results reveal that (1) the average carbon intensity of commercial building operations in 16 countries has maintained an annual decline of 1.94% throughout the period 2000–2019, and emission factors and industrial structures were generally the key to decarbonizing commercial building operations; (2) energy intensity effects have started to promote global decarbonization in commercial building operations since 2010, with contributions from space heating [-14.33 kg of carbon dioxide per square meter per year (kgCO 2 /m2/yr)], service lighting (-5.29 kgCO 2 /m2/yr), appliances and others (-2.85 kgCO 2 /m2/yr), and space cooling (-1.24 kgCO 2 /m2/yr); and (3) the total decarbonization of commercial building operations worldwide was 230.28 mega-tons of carbon dioxide per yr, with a decarbonization efficiency of 10.05% in 2001–2019. Moreover, the robustness of this decarbonization assessment is tested using the typical index decomposition analysis and the decarbonization strategies of global commercial building operations are reviewed. Overall, this study assesses the global historical progress in decarbonizing commercial building operations and closes the relevant gap, and it helps plan the stepwise carbon neutral pathway of future global buildings by the mid-century. [ABSTRACT FROM AUTHOR]

Carbon-reduction effect of the urban residential building sector is crucial to the carbon neutrality target. This study aims to explore the interaction mechanism among influencing factors and simulate the future evolutionary trajectories of urban residential building carbon emissions (URBCE). An integrated dynamic emission assessment (IDEA) model is innovatively established by coupling the system dynamics (SD) model and a bottom-up end-use decomposition model. Combining with the scenario analysis approach, this IDEA model is applied in China's urban residential building sector from 2000 to 2060. Results show that under the baseline scenario, the URBCE will fail to peak before 2030 but will peak at 1.19 Bt CO 2 in 2037. In comparison, it will peak at 0.79 Bt CO 2 in 2025 and decline to 0.17 Bt CO 2 in 2060 under carbon-neutral scenario, which can be neutralized by negative carbon technologies. Different end-uses and climate zones show marked discrepancies in emission-reduction potential, with the contribution of heating and appliances being over 50%. Sensitivity analyses shows that the low-carbon awareness, electrification rate, proportion of clean energy generation and technological progress contribute positively to the early peak of URBCE. This study provides a deeper understanding of China's potential peaking paths and can assist policy-makers in better evaluating emission paths for other nations and regions. [Display omitted] • Develops an IDEA model by combining system dynamics model and LEAP model. • Explores the interaction and feedback mechanism among different levels of factors. • Simulates the URBCE by combining the IDEA model and scenario analysis approach. • Urban residential buildings will peak at 1.19 Bt CO 2 in 2037 under the BAU scenario. • Different end-uses and climate zones show marked discrepancies in emission-reduction potential. [ABSTRACT FROM AUTHOR]

A special cubic spline for histograms was examined as a possible tool for the processing of mass spectrometry data. Algorithms of interpolating and smoothing cubic splines are described shortly. It was shown that peak apex localizations using splines yield similar results as peak apex determinations using parabolas and centroids for high intensity peaks, while for low intensity peaks, the peak apex localizations using splines are superior. It also was shown that peak localization accuracies for real experimental time-of-flight mass spectral data are higher in case of peak localizations that use apex determinations as compared to peaks determined by centroid or Gaussian approximation of peaks. Some examples of peak detection algorithms using splines are given. A new method of peak intensity calculations is proposed taking into account the baseline. All approaches are directly applicable for the processing of TOF MS data, though specific changes may be desirable for other MS data. [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]

(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]