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Daytime subambient radiative cooling is a most promising alternative to electricity-free building cooling. However, optical performance degradation arising from surface contamination and inevitable parasitic heat gain still pose unprecedented challenges to cool building at subambient temperatures. This paper proposed a superhydrophobic cellulose aerogel cooler (SHB-CAC) as building envelope by integrating self-cleaning capacity, passive daytime radiative cooling and thermal insulation to reduce environmental heat gain. The SHB-CAC demonstrates high solar reflectance (93%) and long-wave infrared emittance (91%), accomplishing a temperature drop of 8.5 °C lower than the ambient under sunlight of 800 W/m2 in the outdoor experiment. Notably, the SHB-CAC possesses low thermal conductivity (28 mW/(m∙K)) that suppresses parasitic heat gain from warmer surrounding and reduces cooling energy consumption. The self-cleaning property resulting from superhydrophobicity protects SHB-CAC from water wetting and dust contamination but also maintains its good surface radiation capacities under different humidity environment. A building energy simulation was conducted and results showed that 43.4% of cooling energy on average could be saved compared to the building baseline consumption, if SHB-CAC was widely used in China, indicating that the strategy of optical and thermal conductivity management of cooler has the potential to reduce the energy consumption of buildings. [Display omitted] • Waste paper is converted into aerogel cooler for building cooling. • High R solar and ε IR , thermal insulation, and self-clean are achieved in one design. • The aerogel achieves a high sub-ambient temperature drop of ∼8.5 °C on daytime. • The aerogel shows that 43.4% of cooling energy could be saved. [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]

China is facing the challenge of high building energy consumption, especially for rural housing, because of the backward construction technology. This issue could be solved by net-zero energy rural housing. Therefore, the passive energy-saving procedures and energy-efficient building service systems of rural housing are needed to be studied apart from renewable energy adoption. Older people with unique thermal acceptability and adaptability become the primary residents in Chinese rural buildings, which calls for the redefinition of the indoor environment. This paper firstly conducted an overall questionnaire about the indoor environment sensation and expectations of the rural elderly in Sichuan province. Field surveys and measurements were carried out in a typical self-built rural house to investigate the thermal comfort of the local order people and the indoor thermal environment variations. Furthermore, the fuzzy analytic hierarchy process was used to propose a three-layer assessment model for the rural elderly living environment to find retrofit strategies. Results showed that: (1) the thermal environment of rural buildings could not meet the thermal comfort range of older people in summer. (2) The adaptive coefficient (λ) in the adaptive Predicted Mean Vote model was 0.065 for the rural elderly, which was lower than the value of 0.21 in the Chinese standard, indicating their poor thermal adaptability. (3) The summer living environment evaluation was "A little bad", and the most effective optimization method was to decrease the indoor temperature. (4) Based on the thermal comfort of older people, architectural and construction optimizations were proposed, which could achieve an energy-saving of 52.15 %, contributing to net-zero energy rural housing. • Environment improvement and energy saving of rural housing were studied. • The age-based metabolic rate of the elderly was proposed in aPMV. • The adaptive coefficient for the rural elderly was 0.065. • The evaluation model of rural living environment satisfaction was built by FAHP. • Passive retrofit procedures were proposed to achieve NZERH. [ABSTRACT FROM AUTHOR]

The operational state of energy-efficient ultra-low energy consumption buildings is very important to achieve energy savings and emission reductions, which are currently necessary considerations for the development of the building industry. To date, studies on the implementation of ultra-low energy consumption have been based mainly on the analysis of the effects of certain technologies, and few studies have examined the regional implementation paths at different energy consumption levels. Based on an analysis of actual data obtained from energy consumption monitoring, verification of energy-saving renovations and green building evaluations in Chongqing, this paper suggests setting the target value for ultra-low energy consumption buildings in hot summers and cold winters areas at 29.04 kWh/(m2.a), proposes a technology system that includes the practical application of data for seven active energy-efficient technologies, and establishes an implementation path for the integrated application of active and renewable energy technologies. Then, a set of strategic models for the construction of implementation paths for ultra-low energy consumption buildings that can be promoted in different climatic areas and building types is proposed. The recommendations based on this model are of practical value for guiding policy makers in promoting the development of ultra-low energy consumption buildings. • Determined ULEB target value based on actual Chongqing energy consumption data • Proposed energy-efficient technology system based on effect and cost analysis • Proposed replicable strategic models for implementation path of ULEBs construction [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization in recent years, the area and energy consumption of public buildings are also growing rapidly. As a special comprehensive public building, hospital buildings are characterized by high energy consumption, complex structure and high power of equipment. With China's "carbon neutral, carbon peak" goal and the continuous upgrading and improvement of the medical environment, how to reduce the energy consumption of hospitals is also increasingly important. This paper analyzes the climatic characteristics of the hot summer and warm winter region and the energy consumption characteristics of hospitals in this region, then evaluates them and proposes two energy-saving and carbon-reducing measures, namely, photovoltaic power generation and roof greening. Finally, EnergyPlus simulation is used to study the specific cooling savings of using green roofs and analyze the carbon reduction under different percentages of photovoltaic power generation. The results of the thesis have certain application value for energy saving and carbon reduction in general hospitals in hot summer and warm winter areas. • Characteristics of energy consumption of general hospital in hot summer and warm winter region are analyzed. • The carbon emissions of these hospitals were calculated and analyzed and energy saving options were proposed. • Use EnergyPlus to simulate its green roof and calculate its cooling savings and carbon reduction. • Green roofs can save up to 11.7% of cooling. • Photovoltaic (PV) power generation can reduce total carbon emissions, and when the share of PV power generation varies from 10% to 20%, the total carbon emissions can be reduced by 13.79% to 27.43%. [ABSTRACT FROM AUTHOR]

Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

The significant variation in building׳s energy intensity is partly due to the large number of distributed energy users characterized by heterogeneous lifestyles and nonuniform consumption behaviours. Understanding the degree of variation and its cause is critical to designing appropriate policies for energy efficiency improvement. This paper aims to provide a data-based benchmark of buildings energy performance in China and investigates the facts and causes of large variations in energy consumption across buildings based on updated and harmonised dataset. Specifically, the paper is the first in literature to decompose aggregate heating consumption in northern urban China and reallocate the disaggregate data to relevant residential and commercial building energy use, which makes it consistent to conduct international comparison of building performance in terms of primary energy intensity. It is found that buildings energy performance exhibits a sizeable heterogeneity varying with building typology and climate zones in China. Heating and cooling energy consumption for residential buildings located in HSCW climate zone may differ by a factor of 4–10 depending on the technology and energy supply mode, whereby nontechnical interventions may have significant impacts on total energy demand in the built environment. In particular, our analysis results point to the importance of making greater efforts in the commercial sector. Commercial buildings are found significantly more energy intensive than their residential counterpart, mainly due to the fact that BEE policy has been poorly implemented and architectural design has not been optimised in commercial sector. An estimate suggests that improving energy efficiency in the commercial sector may contribute to one-fifth of total energy savings potentials by 2020 in line with the IEA׳s 450 ppm scenario. It is necessary for Chinese building authorities to incorporate the heterogeneity characteristics across different climate zones and building typologies into BEE policy portfolio to effectively curb energy consumption related carbon emissions. [ABSTRACT FROM AUTHOR]

Construction of conserving campus is necessary to achieve sustainable development. Taking North China University Of Science and Technology for example, this paper proposes systematically how to launch subjects of actual measurement and simulation of energy consumption and the analysis of energy-saving for the energy consumption of campus. On the basis of analysis of the college typical building energy consumption, this paper tests the illumination, noise and formaldehyde concentration of Yifu Library, gives a detailed analysis of the measurement data, and provides the basis for energy saving transformation, operation management and updating equipment.By using a building energy consumption simulation software-eQUEST to simulate and research the energy consumption of Yifu Library, and collecting and collating the 2012-2013 annual water, electricity and gas usage to analyze the above energy data, and obtain the current status and characteristics of campus energy consumption. Finally, by comparing the measured and simulated results, it shows that universities present tremendous potential for energy savings. Therefore, from energy conservation of the technology, management and behavior, the reasonable energy-saving reconstruction measures are put forward. [ABSTRACT FROM AUTHOR]

Windows integrated with PV can provide electrical energy and control the energy flow (heat and light) through the windows. With the objective of evaluate the potential application of window integrated PV in southwest China, the performance of silicon PV windows was comprehensively studied. A test unit was developed to monitor the performance of window integrated PV, then a validated comprehensive approach integrated with heat transfer, optical, electrical and building simulation model was used to comprehensively evaluate the performance of the window integrated PV under various climatic conditions in southwest China. The effects of the air gap on window thermal performance, window orientation, different window-to-wall ratio and coverage ratio of PV cells are evaluated. It was found that a maximum energy saving could be achieved, when the PV window is installed on the south facing façade with a PV cell coverage ratio of 0,87, air gap of 9 mm between the two glazing panes. It was found that a maximum energy saving of 983 kWh was achieved in Lhasa. A highest energy saving ratio of 83% was found in Kunming. The window integrated PV shows good energy saving potential under different climatic conditions in Southwest China. The highlights of this paper could be collected as below: • C-Si PV window with reasonable c-Si cells arrangement was designed. • The energy consumption of the building with PV windows was tested. • The design of STPV façade was optimized by the test and simulation results. • The energy saving potential of c-Si PV window in Southwest China is studied. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

• Obtaining the optimal interpolation method for adjacent sites. • Proposing the method for revising meteorological data at city scale. • Verifying the accuracy of the method by energy consumption simulation. In the development process of building energy conservation design, the correct provision of local Typical Meteorological Year (TMY) data is a prerequisite and basic work to evaluate building energy consumption, which directly affects the fine use of outdoor data for building energy conservation. Based on the recorded and observed data of meteorological stations in China, the acquisition and correction methods of TMY were studied by mathematical statistics and target searching, and the building energy consumption simulation of urban office buildings was conducted to verify the accuracy of the method, including:(1) Reviewed the generation method for TMY and the acquisition of data.(2) Based on the existing TMY data, the best spatial interpolation method of adjacent stations is studied by using the standard deviation method, and the selection method of the best number of stations on a large regional scale is given.(3) An improved method of urban environment TMY is proposed. The dry bulb temperature and relative humidity of the building site are corrected to generate TMY under Urban Heat Island (UHI) effect. The research in this paper improves the coverage and accuracy of urban TMY data and supplies basic research support for building energy-saving designs. [ABSTRACT FROM AUTHOR]

• The data requirements of quota methods are summarized, and a city-scale database containing 670 credible government office buildings is established. • By comparing the processes, the results and applicability, the selection basis of quota methods under different conditions is refined. • A flow chart of the formulation process and method selection of city-level building energy consumption quotas is constructed. • It is proposed that special attention should be paid to the outliers, and the characteristics of outliers in Chongqing are summarized. Energy consumption quota policies are effective management measures to promote energy conservation and emission reduction in China. Cities need to choose an appropriate method to formulate local energy consumption quota standards. This paper is based on the data of 670 government office buildings in Chongqing and the selected quantile method (QM), quota-level method (QLM) and multiple linear regression (MLR) method, which are widely used in the formulation of city-level energy quotas. By comparing their interpretability, evaluation, consistency and stability, the application conditions and applicability of each method are summarized. MLR has the strongest explanatory power but the highest requirements for the technology and information dimensions. The QLM is more explanatory and stable than the QM and is more suitable for the initial stage of energy quota management. When using the QLM, we should consider scientific classifications and reasonable quota levels. Special attention should be given to "outliers" with abnormal evaluations of the quota results. The outliers in Chongqing are characterized as buildings that have been used for more than 10 years and have an area of less than 5000 m2. Finally, this paper constructed a flow chart of the formulation process and method selection to help policymakers better understand how to choose the most appropriate method and identify inefficient buildings. [ABSTRACT FROM AUTHOR]

• A novel vector field-based SVR for building energy consumption prediction (ECP) is proposed. • Nonlinearity of the ECP models is transformed into linearity via vector field-based SVR. • Two high precision, generalization capability, and robustness energy consumption prediction models are established. • A real case study demonstrates the superiority of this study compared with previous studies. Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Data-driven approaches, such as artificial neural networks, support vector regression, gradient boosting regression and extreme learning machine are the most advanced methods for building energy prediction. However, owing to the high nonlinearity between inputs and outputs of building energy consumption prediction models, the aforementioned approaches require improvement with regard to the prediction accuracy, robustness, and generalization ability. To counter these shortcomings, a novel vector field-based support vector regression method is proposed in this paper. Through multi-distortions in the sample data space or high-dimensional feature space mapped by a vector field, the optimal feature space is found, in which the high nonlinearity between inputs and outputs is approximated by linearity. Hence, the proposed method ensures a high accuracy, a generalization ability, and robustness for building energy consumption prediction. A large office building in a coastal town of China is used for a case study, and its summer hourly cooling load data are used as energy consumption data. The results indicate that the proposed method achieves better performance than commonly used methods with regard to the accuracy, robustness, and generalization ability. [ABSTRACT FROM AUTHOR]

• BIM-DB can effectively simulate building performance parameters. • The PSO-RF-NSGA-III hybrid method can be used to predict and optimize building performance. • NSGA can simultaneously optimize energy consumption, carbon emissions and thermal comfort. • The optimal building parameters are different in different regions. Near-zero-energy-consumption buildings (NZEBs) are of great significance for sustainable development, and their design and research have attracted increasing academic attention. To drive and realize the energy saving design and achieve carbon emission and thermal comfort optimization of NZEBs, in this paper, an intelligent optimization method integrating the BIM-DB and PSO-RF-NSGA-III method is established. Multiobjective optimization problems involving NZEBs in four typical climate regions in China are explored. With a typical office building as an example, first, simulation calculations regarding the energy consumption, carbon emissions and indoor thermal comfort in the four climatic regions are performed based on orthogonal tests and BIM-DB. Second, the nonlinear mapping relationships between building design parameters and prediction targets are constructed with the PSO-RF model, which is trained with sample data. The obtained nonlinear mapping relations are used to establish the objective function of NSGA-III, and the multiobjective Pareto-optimal solution set is obtained with the developed PSO-RF-NSGA-III algorithm. Finally, the only optimal solution is determined by using the ideal point method, and reference near-zero-energy-consumption office building parameters are calculated for different climate regions. The conclusions are as follows. (1) The PSO-RF algorithm can efficiently predict building energy consumption, carbon emissions and thermal comfort. In the four regions, the goodness of fit of the three targets is greater than 0.94. (2) Multiobjective optimization can be performed with the proposed RF-NSGA-III intelligent optimization method. After optimizing multiple groups of optimization schemes and adopting energy saving measures, the energy consumption levels in the four climate regions are reduced by 39.72 %, 32.22 %, 26.94 % and 35.37 %, and the other goals are optimized. (3) Index calculations indicate that the optimized building design parameters meet the specified standards for NZEBs, and the main influencing factors and corresponding measures vary from region to region. [ABSTRACT FROM AUTHOR]

This paper proposed a hybrid Logarithmic Mean Divisia Index (LMDI) model that decomposes the change of total energy consumption (TEC) in the building sector to three different dimensions: 1) key influencing effects that include area effect, structure effect, population intensity, value intensity, and energy intensity; 2) three phases that include material production, construction, and operation; and 3) geographically distributed regions. Then, the model was validated in China's building sector based on the data collected from 30 provinces during 2007–2015. The key findings show that: (1) the increased final energy consumption in the building industry accounted for 53.3% of that in China. (2) Building material production contributed the most (69.2%) to the energy changes, followed by building operation (29.6%) and construction (1.2%). (3) The change of TEC was attributed the most to the area effect (90.4%) and the energy intensity effect (42.4%). (4) Zhejiang, Jiangsu, Hubei, Hebei, Fujian and Shandong contributed the most (47%) to the increase of China's building energy use. These findings provide an insightful understanding of the building energy changes and also a quantifiable justification for making building-specific energy policies, which are discussed at the end of the study. [ABSTRACT FROM AUTHOR]

In the tourism industry, hotels and homestay facilities account for considerable amounts of energy consumption and CO 2 emissions. Unlike other types of buildings, occupancy has significant fluctuations over time, while mostly being ignored or using a simple assumption based on energy use intensity or setting the occupancy levels. Due to the lack of occupancy rate information, great uncertainties exist in hotel operations, which leads to erroneous estimates of energy consumption in existing hotel buildings. This paper examines hotel operation practices in China with real occupancy rate data which is critical for reducing the uncertainty of estimating energy consumption patterns. Specifically, this study proposes a two-stage comprehensive and quantitative performance assessment approach for the homestay hotel building considering the system's energy and economic performance simultaneously. Regarding energy performance, there are two key facets to consider: renewable energy penetration and grid impact performance. Additionally, the economic performance (annual income and extra annual investment) of various energy portfolios is evaluated using break-even analysis. The impacts of large fluctuation in occupancy rate on electrical loads are considered and assessed in typical homestay hotels. The proposed assessment approach can comprehensively quantify the impacts of the photovoltaics (PV) areas and battery capacities on the system performance in terms of energy and economics. According to the results of the occupancy-based assessment, the ideal PV area and battery capacity are 400 m2 and 16 kWh, respectively, as opposed to the optimal energy portfolios (PV area 600 m2 and battery capacity 24 kWh) determined from conventional assessment results. [ABSTRACT FROM AUTHOR]

The impact of village morphology on habitats' daily spatiotemporal behavior and building energy consumption is still vague. This research aims to propose a method to reveal how and to what extent village morphology and residents' demographic structure influence farmhouses' occupancy rate and energy consumption. For this purpose, a combined time geography and building energy consumption method was proposed to disclose the relationship among residents' family roles, village morphology and household energy consumption. To explore the occupancy rate of farm-houses with different family members in different village morphology, resident types based on field research (retrospective interviews and aggregation behavior observation) were formulated. Residents with similar time-space behavior seemed as an "agent" and then a specified number of agents are combined into different families for ideal experiments. By placing different households in different villages for multi-factor cross-experiment, the occupancy rates of different households are obtained based on individual time-space behavior patterns, and then the energy consumption of each household under different scenarios is obtained by combining building energy consumption simulation. In addition, the relationship between resident's disposable personal time, local public space' quality, and the house occupancy rate was analyzed. Combined with a case study in Shanghai with 417 valid questionnaires, it can be seen that the method proposed in this paper is effective and villages with high quality public space have the potential to reduce household energy consumption from 2.17% to 38.82% for diverse families. The quantitative result indicated that the occupancy rate is mainly influenced by residents having more disposable personal time, and such space-time behavior is sensitive to village morphology. This study proposed a combined method and case evidence to systematically analyze the complex relationship between resident behavior, the village morphology, and household energy consumption, thus contributing to the sustainable plan and design of the community spatial system. [Display omitted] • Proposed systematic approach to reveal the relationship between morphology and energy. • Energy-saving effect of public space is revealed from villagers' behavior chain. • The influence of the village morphology on energy consumption is between 2.17% and 38.82%. • Alternative mode of villager's space usage in disposable personal time was proved. [ABSTRACT FROM AUTHOR]

Resource over-exploitation and resource depletion have received increasing attentions, especially for industrial regions. In this paper an innovative method that combines emergy analysis and an IPAT (Human Impact Population Affluence Technology) equation is developed in order to create an integrated framework for uncovering the driving forces on resource consumption in one industrial region. Liaoning province, one of the old heavy industrial bases in China, is selected as the case study region. The main results show that total emergy of Liaoning province increased from 9.25E + 23 sej in 2002 to 1.92E + 24 sej in 2012, with 165% growth on non-renewable emergy and 250% growth on imported emergy. Regional emergy/RMB ratio was higher than other developed regions and the average value of China, indicating that this province consumed more local free non-renewable resources to support its own development. The lower ESI (emergy sustainability index) indicates that Liaoning province's sustainability is still weak and far away from sustainable development. IPAT analysis further identifies that rapid economic growth was the main driving force to increase its total emergy use, while technology innovation offset the increase of total emergy use. Policy insights suggest that industrial regions should improve their energy efficiency and optimize their economic and energy structure by applying economic instruments and capacity building efforts. [ABSTRACT FROM AUTHOR]

The spatial distribution of biomass resources is not uniform. At present, the zoning of biomass energy development suitability is primarily based on resource potential, whereas energy demand is ignored as an important factor affecting the degree of local energy self-sufficiency. Under the constraints of high transportation costs, solar energy with low geographical constraints can be a supplementary energy source for biomass despite its instability. Based on the energy utilization potential of solar energy and biomass resources, this paper evaluates the energy surplus factor (ratio of renewable resource potential to energy demand) of each city in the study area, takes meeting the specific energy surplus factor as the construction prerequisites of biomass combined heat and power (CHP) plants, calculates the biomass resource utilization rate and energy surplus factor in the study area under different conditions, and provides zoning suggestions and data reference for the unified planning of biomass CHP plants. The minimum energy surplus factor that is suitable for the development of biomass energy is set as the construction threshold of biomass CHP plants (The construction threshold is the minimum condition for the construction of biomass CHP plants. Only areas where the energy surplus factor reaches the preset construction threshold are allowed to build biomass CHP plants). The results show that the construction threshold is negatively correlated with the utilization rate of biomass resources. When the construction threshold is less than 1.4, the utilization rate of biomass resources decreases rapidly with the increase of the construction threshold; when the construction threshold is greater than 1.4, the utilization rate of biomass resources decreases slowly and tends to be flat. It is suggested that biomass resources should be developed in different regions and in stages, and priority should be given to developing areas with an energy surplus factor greater than 1.4. Areas with an energy surplus factor of 0.3–1.4 are considered secondary development areas, and areas with an energy surplus factor of less than 0.3 are not recommended for development; these can meet 31% and 59% of the total energy demand and reduce 50319380 tons and 180524400 tons carbon emissions so that the limited construction cost can meet higher energy demand and biomass resource utilization. • Priority development areas are identified based on solar and biomass potential. • Energy surplus factor is calculated to determine the development suitability. • Strategies for zoning and phased planning of biomass resources are proposed. [ABSTRACT FROM AUTHOR]

Passive building with solar energy absorption for winter heating is an effective way to reduce building heating energy consumption. In order to solve the problems of uneven indoor temperature distribution and poor thermal comfort that exist in traditional attached sunspace heating, the Attached Sunspace with Breathing Window (ASBW) is studied in this paper. A field investigation and numerical simulation have been conducted on a farmhouse in North China to monitor the variation of indoor temperature. On this basis, three more contemporary ASBW design schemes are proposed, and the characteristics and benefits of the Attached Sunspace with Breathing Window are further studied. The Percentage Dissatisfied (PD) is selected as the index of indoor local thermal comfort to evaluate the performance of the ASBW. The results show that the indoor temperature in the vertical direction increase with the height, with the high-temperature region exceeding 23 °C and the low-temperature region only about 18 °C on sunny days. Simulation analysis of the three schemes revealed that the Bottom outlet scheme and the Top inlet scheme possess better local thermal comfort. The maximum average indoor temperature of both schemes is around 23 °C, and the vertical indoor temperature PD index is significantly reduced to the lowest average value of only about 8% compared to the original design with a single-window of 23.6%. The Bottom outlet scheme and the Top inlet scheme are recommended for the newly-built and existing buildings, respectively. • A design of breathing windows for sunspaces in north China is proposed. • The mechanism of the breathing windows is analyzed by the CFD simulated. • The simulation proves breathing windows can improve indoor local thermal comfort. • Two schemes of the sunspace are nominated for the newly-built and existing buildings. [ABSTRACT FROM AUTHOR]

China has been the world's largest producer and consumer of air conditioners, and more and more RACs 1 1 The RACs is short for room air conditioners. would be owned by China's households along with the rapid economic development. Air Conditioner is also considered as one of the largest potential contributors to energy reduction among home appliances because of the huge energy consumption. Therefore, the national energy efficiency standards were issued to promote the use and production of high-efficient RACs. According to China's energy efficiency standards, this paper investigated the electricity savings and CO 2 emission reductions from RACs over the period of 2005–2025. The results indicate that the rural RAC market which develops more slowly than the urban one still has great potential, and government has to revise subsidy policies to make the standards more effective, especially for rural areas. In 2025, the total electricity consumption of RACs is projected to be 598–674 TW h, while the amount without energy efficiency standards is 753 TW h. From 2005 to 2025, the energy efficiency standards for RACs can save 1430–2540 TW h electricity and reduce 908.3–1610. 1 Mt CO 2 emissions in different scenarios. Finally, we suggest that the standards should be revised every 4 or 5 years with higher revision pace of 8% to 10% [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid urbanization. The building sector plays an important role in China's energy conservation and emission reduction. An increasing amount of energy will be steadily consumed in the building sector as the urbanization process accelerates. China's government attaches great importance to building energy efficiency (BEE). How does the urbanization process affect building energy consumption (BEC)? How much energy can be saved in the building sector through implementation of energy polices? These questions are critical for government development strategies and planning. Thus, in this paper, an econometric model (co-integration technique) is developed to analyze how China's BEC is affected by macroeconomic variables in the context of urbanization, and also forecast the BEC and BEE potential until 2020 under different scenarios. The research result shows that occupants’ lifestyles, residents’ living standards, and energy price have significant influences on BEC. The building sector is likely to contribute approximately 20% to China's energy conservation through electricity pricing reform. [ABSTRACT FROM AUTHOR]

• The degree of influence of residential cluster layout factors on building heating energy consumption levels in cold regions of China. • Provides an idea of residential layout optimization and design based on the energy saving objectives of residential clusters, translating quantitative indicators such as wind environment into residential layout form design problems. • Energy simulation-based residential planning and layout design method is used to quantify the relationship between residential cluster design factors and energy efficiency in Jinan, resulting in optimal design parameters for residential planning factors in Jinan. • The study of building heating energy consumption in a city in a cold region of China, with a methodology that can be used in countries or cities with similar climate characteristics. Residential heating energy consumption in China accounts for about 34% of the total building operation energy consumption in the country. The layout pattern of residential clusters is one of the most critical factors affecting building heating energy consumption, yet few scholars have studied the layout of residential clusters in a quantitative way. This paper takes Jinan, a typical city in cold region IIB of China, as an example, to quantify and analyse the residential layout parameters related to heating energy consumption: group layout, building orientation and building spacing; ECOTECT and HTB2 are used to model and simulate the energy consumption of the three types of layout residential groups selected for the study, and the relationship between residential group layout parameters and residential heating energy consumption is analysed based on multiple linear regression analysis. The relationship between residential group layout parameters and residential heating energy consumption was analysed based on multiple linear regression analysis. The study shows that, on the premise of ensuring the same building density, the group layout has the greatest influence on the building energy consumption, and the courtyard layout has lower heating energy consumption compared to the row and staggered layout; on this basis, the influence of building orientation and building spacing on heating energy consumption is discussed. The study shows that increasing the spacing between buildings to meet the daylight spacing will reduce energy consumption by 4% and that a 15° shift to the west will reduce energy consumption by 5%. This result confirms the importance of cluster layout in terms of heating energy consumption and urban energy efficiency in cities in cold regions. [ABSTRACT FROM AUTHOR]

Abstract: Current energy designs for a building in China focus on the energy efficiency of the whole building and thus often neglect the energy difference between different housing units in apartment buildings. The best design technique in terms of energy savings is not only to decrease whole building energy demand, but also to reduce the energy difference between different housing units to a relatively low level. This paper introduces an important index “energy performance difference between housing units” (EDH) to evaluate the drawbacks of conventional designs on a typical residential building in hot summer and cold winter zone. Then nine improved design options were considered as the possible strategies to diminish the EDH, based on a number of building simulations with the program DeST-h. Results show that the option 9 (add movable shading for the east facing windows and west facing windows, and reduce the U-values of the east walls and west facing windows), an improved design strategy according to the EDH of the current design, reduces the EDH to less than 4% that is much lower than other options and meanwhile ensures a decrease in whole building energy demands. A case study was carried out to validate the effectiveness of this index in optimization. As a conclusion, EDH is a very useful index for optimizing energy designs of apartment buildings and can be used in China to improve conventional building designs. [Copyright &y& Elsevier]

• Two-year monitoring campaign of IEQ parameters of a nearly zero energy building was firstly presented in China. • The nearly zero energy building can provide the indoor with a comfortable thermal environment and good air quality with less energy demand. • The overheating problem in the whole year would be especially paid attention during design and operation. • The occupant behavior has a significant impact on energy consumption and thermal comfort. The paper presents a two-year field measurement and assessment of a nearly zero-energy Building in cold zones of China. These parameters of indoor environment quality (IEQ) and electricity consumption for HVAC are recorded. According to the measurement data, the most of indoor temperature was controlled in the range of 23 °C ~ 26 °C and relative humidity (RH) mainly fluctuates within the range of 30% ~ 60%. The concentrations of carbon dioxide (CO 2) and particulate matter (PM 2.5) are lower than the relevant standard requirements in most of the time. The average electricity consumption for HVAC was 33.05kWh/(m2·a) and the heating and cooling demands could be reduced by 55.2% and 54.0%, respectively, compared with existing buildings. In general, the NZEB can provide indoor comfortable thermal environment and indoor air quality with less energy demand, but the overheating problem in summer and effect of occupant behavior should be especially paid attention during operation. Overall, the experience from the actual operation of NZEBs will help China to reach its goals of reducing carbon emissions and addressing climate change through realizing the energy-saving potential of NZEBs. [ABSTRACT FROM AUTHOR]

China is committed to peaking its carbon emissions by 2030 and become a carbon-neutral society by 2060. The building sector that accounts for over one-third of the total carbon emissions is expected to face a great challenge in helping China achieve this goal. Shenzhen, as a low-carbon pilot city, whether its low-carbon work of urban buildings reaches the target is crucial. An attempt has been made in this study to assess the intensity of carbon emissions and associated reduction efficiency of urban buildings (operation stage) in Shenzhen by using the life cycle assessment method. The results show that the total carbon emissions generated from the buildings' operation stage have increased from 22 million metric tons (Mt) CO 2 eq in 2005 to 42 (±13%) Mt. CO 2 eq in 2019. Carbon emissions mainly result from the buildings' electricity use (79%), followed by refrigerant release emissions (12%). The energy conservation and carbon emissions reduction intensity in Shenzhen is at the middle level in China, and there is considerable space for improvement. According to scenario-based analysis, the carbon emission of the buildings sector can probably reach its peak by 2025 with the implementation of suitable policies – 5 years earlier than national target by 2030. Overall, this study makes a systemic analysis of the characteristics of urban buildings energy consumption and carbon emissions reduction, which can provide supportings for justifying the effectiveness of low-carbon activities in Shenzhen and beyond. • This paper evaluated the emissions reduction of civil buildings in Shenzhen city. • LCA method is employed to quantify the efficiency of emissions reduction. • Public buildings consume more energy per unit area than residential buildings. • Electricity use is the focus of buildings emission, accounting for 79% of the total. • Current efforts cannot meet the ambitious carbon peak and neutrality target. [ABSTRACT FROM AUTHOR]

The building envelope performance significantly influences the building energy consumption, and the major influencing factors of the building envelope include the external wall U-value, external wall solar absorptance, roof U-value, roof solar absorptance, external window U-value, and window-to-wall ratio. This paper proposed a framework that integrates Building Information Modeling (BIM) with LSSVM (least square support vector machine (LSSVM) and non-dominated sorting genetic algorithm-II (NSGA-II) to study the influence of building envelope parameters on building energy consumption and discover the best design. The DesignBuilder (DB) is used to perform energy consumption simulation and orthogonal experiment to obtain the sample data set. The LSSVM is utilized to learn the data set to establish a prediction model between the building envelope and energy consumption, which is used as the fitness function of the building energy consumption in NSGA-II. With the objective of minimizing building energy consumption and maximizing the indoor thermal comfort (measured by predicted mean vote or PMV), an NSGA-II multi-objective optimization model is established. The Pareto front is obtained through calculation, and the optimal combination of building envelope parameters is discovered using the ideal point method. A case of a proposed school building in China is used to demonstrate the feasibility and effectiveness of the developed framework, the results show that: (1) The LSSVM has great ability to predict building energy consumption, achieving an accurate prediction with a goodness-of-fit of 0.9549 and an RMSE of 0.0273; (2) The optimized envelope design parameters of the proposed building are presented, including the External wall U-value is 0.2, the External wall solar absorptance is 0.55, the Roof U-value is 0.2, the External window U-value is 0.4166, the External window U-value is 1, the Window-wall ratio is 0.215. (3) The developed LSSVM-NSGA II hybrid approach can effectively improve the building's energy consumption and thermal comfort with the building energy consumption reduced by 10.6% and the thermal comfort increased by 32.2% than the initial values, respectively. The proposed LSSVM-NSGA II framework is able to optimize building envelope design parameters than its precedent, which can provide effective thinking for similar problems. • LSSVM-NSGA-II hybrid method can predict and optimize the building energy consumption. • The energy consumption prediction surrogate model trained by LSSVM is an efficient NSGA-II fitness function. • NSGA can effectively reduce building energy consumption and improve thermal comfort at the same time. [ABSTRACT FROM AUTHOR]

As one of the three major fields of building energy consumption, public buildings (PBs)are under pressure regarding energy saving and emission reductions, with PB energy consumption accounting for 38% of the total consumption. Thus, CO 2 emissions released in PBs have become crucial for China in achieving its emission mitigation goal in the "Post Paris" period. This paper is the first to develop a support vector machine (SVM) method to predict and diagnose PB energy consumption based on 11 input parameters, including historical energy consumption data, climatic factors and time-cycle factors. Months with air-conditioning energy consumption in Wuhan were considered the study period, and we used June and July data for model prediction training, August data as the test set, and September data to diagnose the air conditioner energy consumption anomaly. The results show that air conditioning energy consumption was abnormal for four days in September. Relevant policies and suggestions are proposed based on the causal analysis. This research is expected to provide theoretical guidance and a practical data reference for building operations management. [ABSTRACT FROM AUTHOR]

• The energy consumption levels of various types of traffic buildings in China are revealed based on a large sample survey. • Energy consumption per unit area is proposed as a reasonable evaluation index of traffic building energy consumption. • Building energy consumption throughout the year is split according to characteristics. Airport terminal, railway station, and subway station are public traffic buildings with special functions, which are responsible to satisfy the basic needs during the use of public transportation. In this paper, the current status of building energy consumption and appropriate energy consumption evaluation methods for these traffic buildings in China are studied. The energy consumption levels of various types of traffic buildings in China are firstly revealed based on a large sample survey, and an analysis method for the energy use of such buildings is then proposed. It's found that the average annual energy consumptions for these three types of buildings are 206.3 kW h/(m2·year), 115.7 kW h/(m2·year) and 124.9 kW h/(m2·year) respectively. The energy consumptions of traffic buildings in the hot summer and cold winter zone and hot summer and warm winter zone are manifested to be higher mainly due to the climate characteristic. Besides, energy consumption per unit area is considered to be the most suitable indicator for an accurate assessment. The energy evaluation method for traffic buildings is proposed where the total energy is divided into the basic energy and variable energy. The basic energy consumption is mainly related to the building function for transportation, while the variable energy consumption is mainly determined by the local climate. It's found the basic energy consumption accounts for about 50 % of the airport terminals and railway stations. The energy use indexes for different traffic buildings are also obtained based on the surveyed results. [ABSTRACT FROM AUTHOR]

Energy Consumption monitoring technology (ECMT) can effectively reduce the energy consumption of public buildings (PB) in the operational phase, but it is not used widely in China. The main reason for this is that the existing policies have a poor effect on diffusing ECMT; thus, studying the impact of different policy instruments on ECMT in PB is of great significance to the widespread use of ECMT and its role in decreasing the energy consumption of PB. This paper systematically reviews the policy related to ECMT in China from 1990 to 2018, and, on this basis, divides the promotion stage of China's ECMT into three stages: the concept stage, the demonstration stage and the gradual promotion stage. A questionnaire survey and semi-structured interview of 313 stakeholders (ECMT suppliers, government officials, and scholars) was used to study the influence of command-and-control instruments (CAC), economic incentive instruments (EI) and exhortatory instruments (EXI) on the diffusion of ECMT in PB. The empirical results show that CAC and EXI contribute to the diffusion of ECMT in PB, whereas EI do not. In more detail, laws and regulations, energy consumption quotes, education and information programs, and energy audits and disclosure also have a significant impact on diffusing ECMT, whereas technical standards, subsidies for adopting ECMT, energy performance contracting, and carbon trading do not. Finally, relevant policies and suggestions are put forward based on the results. [ABSTRACT FROM AUTHOR]

As China takes great efforts to cap its total energy consumption, it is important to understand the future energy use in all sectors. This paper aims to present a long-term prediction of energy use in China's construction and building sectors (CBS) up to the year 2100. A STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model is used to establish the relationship between six socioeconomic and technological factors and China's CBS energy consumption. Based on the statistical data from 2000 to 2016, ridge regression is applied to derive the coefficients of the STIRPAT model to counter the impact of multicollinearity on regression results. The projections are performed for three scenarios: a benchmark scenario, an intensive scenario, and an extensive scenario. The results show that for all three scenarios, the overall trend of China's CBS energy consumption is to continuously increase from the present, reach a peak in the range between 1155 and 1243 million tons of standard coal equivalent (Mtce) in 2050, and then decrease to 942–1116 Mtce in 2100. The above projection and the associated STIRPAT model are valuable for developing policies on construction and buildings to control the total energy use in China. • Use a STIRPAT model to predict China's energy use in construction and buildings. • Three scenarios and six socioeconomic and technological factors are considered. • The projected energy will increase until 2050 and then decrease gradually. • A peak energy use between 1155 and 1243 Mtce is projected to occur in 2050. [ABSTRACT FROM AUTHOR]

• We selected three benchmarking methods to establish building energy benchmarking models based on a sample of 45 hotel buildings in China. • We compared the three benchmarking methods in terms of consistency, robustness and explanatory ability. • The energy efficiency performance obtained from the three methods were found to be inconsistent. • We came up with suggestions based on comparative analysis for policy-makers to develop building energy benchmarking programs. A reasonable building energy efficiency benchmarking program plays an important role in energy consumption control and supervision. Previous studies have focused on the process of establishing a single benchmarking method, but few have compared the performances and outcomes of different methods. To fill this gap, this paper selects three benchmarking methods—multiple linear regression (MLR) based on Energy Star, stochastic frontier analysis (SFA) and the descriptive statistics method (DSM) based on the national energy consumption standard in China—to develop benchmarking models. We demonstrate each method using data on the energy and building characteristics of 45 four- and five-star hotel buildings located in Chongqing, China. To compare the consistency, robustness and explanatory ability of the three methods, we first utilize the Spearman rank correlation analysis to test whether these methods have consistent energy efficiency ranks and then present Sankey diagrams to further reveal the interactions of the estimated energy efficiency grades obtained from the three methods. It is found that the results of DSM and SFA are most consistent, while MLR vs. SFA and MLR vs. DSM present significant differences in evaluating building energy performance. In addition, DSM is more robust for evaluating the ranks of sampled buildings, while SFA is more robust for evaluating energy efficiency grades. Furthermore, we discuss the explanatory ability of each method. In addition to the building characteristics, the design and operational characteristics of the HVAC system have great effects on building energy consumption. Finally, we present suggestions for policy-makers regarding the development and implementation of the building energy benchmarking program in Chongqing and for the management of buildings with different energy performances to further improve the energy efficiency. [ABSTRACT FROM AUTHOR]