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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]

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

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

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

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

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

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

This study measures the "real" total-factor energy efficiency (TFEE) of the construction industry with data from 30 Chinese provinces (excluding Tibet) from 2006 to 2015 using the DEA model combined with the TFEE algorithm. The floor space under construction is considered to be an output indicator in addition to the traditional economic output under the TFEE framework. Next, the spatial distribution of the TFEE of construction industry among those provinces is detected and possible reasons are analyzed. Results indicate that, most of Chinese provincial regions are energy inefficient in construction industry during the research period. Conversely, the three provinces of Beijing, Hainan and Zhejiang have optimal efficiency, which constitutes the efficiency frontier of energy consumption throughout China. There exists divergence among 30 provinces and three regions as for TFEE, but the divergence decreases and manifests the convergence feature. Moreover, among the three main regions, central and eastern regions' TFEE of the construction industry are higher than the figure for the western region. By comparison, we found that the TFEE evaluation considering floor space under construction is more accurate and rational than without considering the floor space. On the basis of these findings, some policy implications are provided for improving Chinese energy efficiency, especially for less developed regions. [ABSTRACT FROM AUTHOR]

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

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]

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]

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]

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]

[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]

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]