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Social progress and economic development has resulted in the need to focus on the impacts of building microenvironment on the energy consumption in office buildings. The concept of a building's microenvironment was introduced to understand the local microclimate around a building that is formed by the surrounding urban green spaces, the distribution of roads, and building proximity. For this research, we adopted a regression analysis to quantify the impacts of building microenvironment on energy consumption in office buildings. Taking the government office buildings of Guangdong Province as an example, we measured the building microenvironment through the urban green space density, road density, and number of points of interest (POI) around the buildings. The results showed that when the green space density increased by one unit, the energy consumption in government office buildings was reduced by 0.277%. Moreover, an increase of 1% in road density and in the number of POI increased the energy consumption in government office buildings by 0.288% and 0.048%, respectively. Furthermore, we discussed the heterogeneous impacts of building microenvironment on the energy consumption in government office buildings at varying scale levels. Green space and road density had less impact on the energy consumption in larger buildings, whereas the number of POI had no significant impact on small-scale buildings but did have a significant impact on large-scale buildings. There were also some limitations in the study. The data were limited to government office buildings, and did not include panel data, as well as it lacked building characteristics such as orientation, floor height, and building materials. In addition, it was impossible to evaluate the impacts of meteorological factors such as wind speed and thermal radiation on energy consumption in buildings. Nonetheless, our study demonstrates that energy-aware urban planning and design have the potential to unlock energy efficiency for cities worldwide. [ABSTRACT FROM AUTHOR]

As the pillar industry of the national economy, the construction industry contributes to economic growth while consuming large amounts of energy and generating carbon emissions. This study adopted the generalized Divisia index method (GDIM) to decompose carbon emissions in the construction industry (CECI) of China and its 30 provinces. A decoupling effort index based on factor decomposition was constructed to analyze the drivers of changes in the CECI and decoupling states during 2000–2020. The results were as follows. (1) The output scale was the main driver for increasing CECI, whereas the carbon intensities of area and output were the largest contributors to decreasing CECI. (2) The national construction industry showed expansive negative decoupling during the 10th–13th FYPs (Five-Year Plans). The decoupling states of provinces showed significant spatial and temporal differences, with most provinces showing negative decoupling and the number of decoupled provinces peaking in the 12th FYP. (3) The scale effect was the key inhibiting factor in the decoupling process of most provinces, while the intensity effect was the main promoting factor, and the efficiency effect was weak. The inhibitory effect of scale gradually weakened, while the promoting effect of intensity increased. Overall, this study expands on current research related to the driving factors of CECI and provides valuable insights into the low-carbon development of the construction industry in other emerging countries. • A GDIM-based decoupling analysis was applied to the construction industry. • The output scale and area scale were the key factors that increased carbon emissions. • Most provincial construction industries showed negative decoupling. • Efforts to promote decoupling should focus more on intensity and efficiency effects. [ABSTRACT FROM AUTHOR]

As the energy demand of public building (PB) in China continues to increase, it is meaningful for forecasting the future trend of carbon emissions (CE) of PB. This study analyzes the drivers of CE that affect the operational stage of PB in China by the Generalized Divisia Index Method (GDIM), which considers the effect of the output value and structural transformation of the tertiary industry and makes a scenario prediction of the future carbon-neutral trajectory of CE in PB under the Shared Socioeconomic Pathway (SSP). The results show that from 2010 to 2020, the added value of the tertiary industry (AVTI) is the strongest positive driver of CE from PB (31.912% of the total contribution), which correspond to a cumulative contribution of 212.3 million tons (MtCO 2) in 11 years. Regulating the CE per unit of the AVTI is the key indicator in reducing CE from PB, with a cumulative reduction of 130.1 MtCO 2. The results of the five scenarios under the SSP framework differ significantly, with SSP1 peaking first in 2026 at 884.5 MtCO 2 (876.2–893.9 MtCO 2) and SSP5 peaking latest in 2049 at 1372.3 MtCO 2 (1362-1389.7 MtCO 2). SSP1 yielded the smallest projection in 2060 with 189.8 MtCO 2 (185.4–194.3 MtCO 2). The findings could help public buildings to implement carbon reduction and provide more scientific and rational decision support for possible paths to achieve carbon neutrality in China. • Projection of carbon emission changes in China's public building operation phase to 2060. • The GDIM which considers the added value of the tertiary industry and industrial transformation factors are employed. • Added value of tertiary industry is essential to the change of carbon emissions. • Carbon emissions of public buildings peak first in 2026 and are lowest in 2060 under the SSP1 scenario. [ABSTRACT FROM AUTHOR]

Due to large energy consumption and carbon emissions (ECCE) in the building sector, there is huge potential for carbon emission reduction, and this will strongly influence peak carbon emissions and carbon neutrality in the future. To get a better sense of the current research situation and future trends and to provide a valuable reference and guidance for subsequent research, this study presents a summary of carbon peak and carbon neutrality (CPCN) in buildings using a bibliometric approach. Three areas are addressed in the review through the analysis of 364 articles published from 1990–2021: (1) Which countries, institutions, and individuals have conducted extensive and in-depth research on CPCN in buildings, and what is the status quo of their collaboration and contributions? (2) What subjects and topics have aroused wide interest and enthusiasm among scholars, and what are their time trajectories? (3) What journals and authors have grabbed the attention of many scholars, and what are the research directions related to them? Moreover, we propose future research directions. Filling these gaps will enrich the research body of CPCN and overcome current limitations by developing more methods and exploring other practical applications. [ABSTRACT FROM AUTHOR]

Soaring building heating energy consumption (BHEC), along with rising income, is threatening carbon abatement efforts. However, the influencing mechanism of income on BHEC remains unclear. This study establishes a theoretical model of the impact of income on BHEC from three perspectives: building physical characteristics, building use characteristics and energy-consuming equipment characteristics. Then, we adopt a stepwise hierarchical regression method to examine the direct and intermediary effects between income and BHEC using microdata from 662 households in Chongqing, China. The results show that household income, residential building floor space, the amount of heating equipment, building energy efficiency standards, and the heating method significantly impact BHEC. Moreover, the direct effect of income on BHEC is up to 84%. The amount of heating equipment and residential building floor space are both strong intermediaries between income and BHEC, contributing 18.8% and 15.8%, respectively. The heating method is a weak intermediary, only contributing approximately 1% of the impact. Overall, this study can promote the development of the related theory of BHEC and provide a reference for the government to implement more effective energy-efficient policies on the local scale and even on the national and global scales. • A splitting model-based calculation method is developed to estimate heating energy consumption • A theoretical model is established to examine the impact of income on heating energy use • The impact of income on heating energy consumption is examined with micro-evidence • Income affects heating energy use through two paths of direct and indirect effects • The number of heating equipment and floor space are both strong mediating variables [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]

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]

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]

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]

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–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]