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The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [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]

• A new spray cooling system is proposed based on PV/T and heat recovery in sow houses. • A simulation model is developed to dimension the new system. • The maximum error is less than 7.2% for the key equipment models in the new system. • The optimal operating ranges of new system are determined in five climate regions. • The operating control suggestions of new system are obtained in five climate regions. In this paper, a new spray cooling system (NSCS) is proposed based on PV/T and heat recovery in sow houses. It contributes to improving system applicability in high-humidity areas and reducing system energy consumption due to solar dehumidification and heat recovery. Meanwhile, the simulation model of NSCS is established and the reliability is verified for the models of its key equipment. The results show that the maximum error is less than 7.2% for the models. The optimal control parameter ranges are further determined for NSCS in five climate regions in China through simulation. The results show that in hot-summer and warm-winter (HSWW) region or hot-summer and cold-winter (HSCW) region, the optimal operating ranges are 40–45 kW and 7245–9245 kg/h for spray power and mass flow rate of circulating water, respectively. However, they are 25–30 kW and 13245–15245 kg/h in other three climate regions, respectively. Finally, the annual performance parameters are compared for NSCS in five typical cities. The regional applicability and operating control suggestions are further obtained for NSCS in five climate regions. The results show that the heat recovery coefficient and energy efficiency ratio are the maximum when NSCS is operated in HSWW and HSCW regions. In high-temperature and arid regions, removing desiccant wheel from NSCS may be a good method to reduce system investment and energy consumption. Meanwhile, the surplus electric and thermal energy can be used for regional energy utilization in NSCS. The above conclusions can determine the regional applicability of NSCS and guide its operating control in different climate regions. [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]

In recent years, water-side free cooling has been broadly applied in data centers to lessen the high cost of energy consumption. The energy-saving opportunities of free cooling have been recognized by numerous studies across the world. In this paper, the field test and energy performance evaluation were performed in an operational data center with water-side free cooling, located in Chongqing, China. Existing problems were found during tests, including the insufficient cooling capacity of towers in wintertime and the inability to activate partial-free cooling. The results of the tests show that the reduction in Power Usage Effectiveness (PUE) is much lower than the expected. To understand the marked discrepancies, the performance of the cooling tower was discussed in terms of the approach temperature and actual cooling capacity. The maximum cooling capacity in winter is only about 50 % of the rated. With the consideration of the cooling tower configuration performance in different climate conditions, the conservative energy effects were calculated in 34 provincial cities of China. To prolong the hours available, optimized operation schemes of cooling towers are presented. The available hours for free cooling could be increased from 730 h to 1300 h when operating at 67 % of rated flow rate, resulting in a decrease in the energy saving of chillers between 8.44 % and 21.05 %. [ABSTRACT FROM AUTHOR]

Glued Laminated Bamboo (GluBam) has been innovated under the support of modern industrial technology, and this renewable material can drive the development of building structural system in a fashion of low carbon footprint. From the perspective of carbon emission, energy consumption and cost-based economy, this paper presents a comprehensive life cycle assessment (LCA) of steel-GluBam hybrid truss and virtually designed steel truss for a comparison. A steel-GluBam hybrid truss constructed at the Nanjing Tech University is used to carry on this study. The system boundary (i.e., production phase, transportation phase, construction phase, operation phase and disposal phase) of life cycle are fist determined. The mechanical properties of the truss structure are considered as the functional equivalence. The inventory of construction materials and the elements in each phase in the life cycle is compiled from the SimaPro and the available literature/specification. Based on the inventory analysis, the Monte Carlo method is employed to conduct the uncertainty analysis of carbon emission of the truss. The assessment results show that the life cycle carbon emission, energy consumption and cost of the steel-GluBam hybrid truss are equal to 4572.5 kgCO 2eq , 71.15 GJ and 15626.6 CNY, respectively. The production phase is the largest contributor to the carbon emission, energy consumption and cost, and the following one is the operation phase. Whereas the transportation phase, the construction phase and the disposal phase together contribute to only the small parts of emissions and cost. GluBam has the function of carbon sequestration leading to the reduction of carbon emission and energy consumption in the production phase, and other phases have no advantage on the emissions and cost of GluBam. The 95% confidence interval of life cycle carbon emission based on the Monte Carlo simulation is estimated as [4290,6370] kgCO 2eq for the steel-GluBam hybrid truss. With respect to the whole life cycle, using GluBam to replace the steel pipe in the upper chord pole and the diagonal web pole of the truss has a little larger cost but its environmental impact and energy consumption reduce a lot. The railway transportation of GluBam reduces 36.5 kgCO 2eq carbon emission, 0.68 GJ energy consumption and 83.7 CNY cost in the life cycle with reference to the road transportation. The steel-GluBam hybrid truss optimized based on the functional unit occurs in the case of reducing the cross-section of steel pipe from 42 mm × 4 mm to 32 mm × 2.5 mm. [ABSTRACT FROM AUTHOR]

Energy efficiency standards for household appliances have been adopted in many countries to mitigate negative externalities, reduce emissions, and save energy. Using Chinese provincial-level panel data from 2008 to 2018, this paper builds a difference-in-difference model to examine the mechanism by which energy-efficiency upgrades in China's air conditioners affect urban household electricity usage. The results show that the upgrades have brought about an obvious reverse effect, with urban household electricity usage increasing rather than decreasing. Reducing the unit costs of energy service has enhanced residents' sensitivity to cooling demand. Driven by the substitution and income effects, urban residents may increase the intensity and frequency of their AC use. Additionally, this reverse effect is heterogeneously dependent on the family size and urban residents' age structure rather than their educational level. When families are larger and have more children, the reverse effect is more pronounced. This paper's findings provide useful recommendations for policy-makers to formulate policies that are synergistic with energy efficiency standards for household appliances. [ABSTRACT FROM AUTHOR]

Abstract In the last two decades, a remarkable socio-economic transition has been witnessed in China. Existing studies have only shown that energy consumption of residents is influenced by economic growth and urbanization. It is unclear, however, how socio-economic transition influences the inequality of energy consumption among urban and rural residents. Focusing on the empirical investigation of two different regions (the eastern developed provinces with little energy resources and the western underdeveloped provinces with rich energy resources), this paper examined the major socioeconomic determinants of energy consumption inequality between urban and rural residents. The results of panel data analyses showed that there was a long-term relationship between socio-economic transition and changes in the inequality of energy consumption among residents. Meanwhile, the results revealed that the influence of socio-economic transition varied from regions to regions. Generally, the influence of urbanization on the inequality of both quantity and diversity was found to be the most profound and significant in all regions. The industrialization transition also exerted far-reaching effects, although its influence was determined by the growth of industry sectors. Moreover, the influence of economic transition was only significant in underdeveloped regions and such an influence fitted to a Kuznet's curve. For the transition of technology and education, its influence was significant in the developed provinces but was only effective in affecting the diversity of inequality. In summary, the findings of this research present policymakers a better understanding of the relationship between the socio-economic transition and inequality in energy consumption. [ABSTRACT FROM AUTHOR]

This paper investigates the climate change impact on cooling energy consumption of office buildings in four major architectural climate zones in China. The results show that there are apparent differences in the responses of monthly or yearly cooling loads to climatic change in different climates. Dominant factors affecting monthly cooling loads change from dry bulb temperature (DBT) to wet bulb temperature (WBT) with the climate zones changing from severe cold to hot. The yearly cooling load was mainly afftectd by DBT in severe cold climate, whereas the WBT had the dominant effect in the other climates. With the continuous warming climate, the yearly cooling load did not rise significantly for any climate zone except for severe cold climate zone where cooling load had a significant increase ( p  < 0.01). More importantly, the cooling load showed a weak decrease in Guangzhou. These results suggest that different measurements for buildings cooling energy conservation should be made in different climate zones. The humidity effect should be fully considered to improve buildings energy efficiency, especially in the hot climate zones. The continuous increase of temperature in the future does not necessarily increase cooling loads of buildings in the cold, hot summer & cold winter and hot summer & warm winter climate zones, and change trendency of humidity in the future need to be considered to predict cooling energy consumption. [ABSTRACT FROM AUTHOR]

In order to resolve the contradiction between the lack of building energy data and the need of more detailed information about energy performance, this paper presents a simplified building energy performance diagnosis method which can assess the energy performance from building level to system level with only limited information. Based on multiple-parameter regression between the whole building energy bills and outdoor weather data, the proposed diagnosis method uses the regression coefficients to identify the energy use of main systems (i.e., lighting-plug system and cooling/heating system), as well as other detailed information about physical properties of the building and cooling/heating system (i.e., cooling or heating load, the operation of cooling/heating system and the efficiency of cooling/heating system). One case study was conducted in an office building in China to test the application of this diagnosis method. In addition, the regression result of simulated energy consumption served as benchmark data to further diagnose the performance gap between the operation stage and the design stage and help locate the poor performance and key points of energy-saving. Finally, all diagnosis results have been verified by the performance data from advanced energy consumption monitoring system together with field surveys and measurements. [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]

• 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 new urban building energy modeling tool-AutoBPS was developed. • AutoBPS calculated urban building energy demands, analyzed energy retrofit and rooftop PV potential via EnergyPlus. • AutoBPS automatically generated multi-zone models, considering shading from surrounding buildings. • A downtown district of 3633 buildings in Changsha, China, was simulated to demonstrate the tool's features. • All three energy conservation measures and PV installation could save 38.6% of total energy demand. China has promised to peak carbon emissions by 2030 and become carbon neutral before 2060. Achieving this target requires actions from all sectors, especially the building sector, which accounts for 33 % of the total energy consumption in China. Within this scenario, this paper introduces a new urban building energy modeling tool, Automated Building Performance Simulation (AutoBPS), to calculate urban building energy demands and to analyze energy retrofit and rooftop photovoltaic (PV) potential. AutoBPS uses a building-by-building approach to automatically generate multi-zone (one zone per floor) models based on the city building dataset, considering the shading effect by surrounding buildings. The tool simulates building energy use and PV generation via EnergyPlus. A downtown district of 3633 buildings in Changsha, China, was selected as a case study to demonstrate the features of the tool. Firstly, annual baseline energy uses of 1793 GWh were simulated by inputting Geographic Information System (GIS) data. Then, different energy conservation measures (covering envelope, lighting, cooling system upgrade, etc.) and roof PV generation systems were adopted to explore energy saving potential. The results showed that the window upgrade was the most energy-efficient individual measure for residential buildings, while the lighting upgrade was that one for commercial buildings. Altogether three measures could save 2.7 ∼ 30.7 % of annual site energy use intensity per building. The total energy demand could be reduced by 18.5 % by combining all measures and saved by 38.6 % when PV installation was added. AutoBPS can be easily applied to other cities, supporting urban energy efficiency plans for carbon reduction goal implementation. [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]

With increasing concern for building energy efficiency, domestic hot water (DHW) supply systems, which have significant energy-saving potential, have drawn more attention from both practitioners and academia. In this study, we conducted a field study on seven centralized hot water supply systems in Beijing, measuring the water temperature and flow rate in primary or secondary pipes and collecting the operating records of hot water usage, gas consumption, and electricity consumption. In addition, we discuss the main problems existing in the current centralized DHW system. Based on measured data, this paper further analyzes energy losses from each link in the hot water supply system. A mathematical model is then proposed for simulating the energy consumption of hot water supply systems under various conditions such as various boiler efficiency, thermal insulation thickness, water pipe network structure, and hot water usage. The model is also used to explore the main factors that lead to low performance of centralized DHW systems in China. Finally, we analyze the applicability of diverse heat sources (e.g., electricity, gas, and heat pumps) in centralized DHW systems in China. [ABSTRACT FROM AUTHOR]

The large public building energy consumption (BEC) is the focus of Building Energy Saving, therefore, it is necessary to study the characteristics of BEC to find out the important factors affecting BEC. For this purpose, 27 office buildings in the west of Inner Mongolia Autonomous Region were studied, based on statistical analysis of the researched basic information and energy consumption bill of these buildings. This paper focused on the determination of the significant factors affecting the total and subentry energy consumption intensity (ECI) of office building, as well as the establishment of standardized linear regression models between these selected factors and total and subentry ECI. Firstly, eleven continuous variables, three independent categorical variables, and the climate factor were selected and analyzed the impact on total and subentry ECI by statistical software SPSS20.0, in order to find out the significant influencing factors. Then based on the results of curve fitting, standardized models of total and subentry ECI and their respective significant impact factors were established using multiple linear regression analysis. The regression results showed that the electricity use percentage of the total equivalent electricity consumption was an important factor affecting the total ECI of office building in the west of Inner Mongolia Autonomous Region. Finally, univariate analysis of variance (ANOVA) was conducted between the three independent categorical variables and the total and subentry ECI, and the results showed that these factors had no significant effect on the ECI of office building. Process of the regressive model establishment and the results of analysis of variance could both guide us to propose more targeted energy saving measures. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

Under the background of global warming, the world is experiencing many extreme climate events. The temperature fluctuation associated with climate change is often considered as a primary driving force of electricity consumption. To better explore the impact of temperature on electricity consumption, this paper aims to analyze the question from the perspective of income growth, i.e., the moderating effect of income growth on the response of urban residential electricity to temperature changes. Using the unbalanced panel data of 23 cities in the Yangtze River Delta Urban Agglomeration from 2004 to 2015, we construct the response model of residential electricity consumption to income growth, heating degree days, cooling degree days and their interactions. The results show that heating demand, cooling demand and income growth significantly increase residential energy consumption. However, urban residential disposable income growth weakens the positive effect of heating demand and cooling demand on residential electricity consumption. Because, urban residents have obvious demand for improving indoor heating comfort and cooling comfort, the moderating effect of income is shown as the crowding-out effect. Residents may adjust the structure of heating energy consumption (from electricity to natural gas) and upgrade their electrical equipment to high energy efficiency equipment, thereby reducing residential electricity consumption. This study also indicates that urban residential energy consumption is very sensitive to changes in permanent populations. The main contribution of this study is proposing the hypothesis of the negative moderating effect of income growth on temperature changes and expanding the response model of residential electricity consumption to temperature changes. Finally, this paper also proposes the adaptive strategies and policy implications for climate change. [ABSTRACT FROM AUTHOR]

• A novel three-stage decision-making approach for office buildings design considering 'Energy','Comfort', and 'Cost'. • The establishment of an optimization and decision-making model by applying NSGA-II and TOPSIS methods. • Two-year monitored data and post-occupancy evaluation for energy audit and thermal comfort. • The evidence of a case study demonstrates the feasibility of the proposed method and solutions. China, with the largest energy consumption system in the world, faces numerous challenges in achieving the government's commitment to reach a carbon-peak and carbon–neutral target. As the most common public building type in terms of floor area, office buildings have great potential for energy saving and emissions reduction. To meet this target, building designers target passive solutions that can meet the thermal comfort needs of occupants and also reduce energy consumption. This study aims to develop a decision-making method to select optimal solutions from among tens of thousands of design options considering the factors of energy consumption, comfort, and cost. We developed a novel optimization decision approach with the above-mentioned three objectives. The model consists of three stages: 1) the establishment of the reference building model, 2) sensitivity analysis to identify the main influencing variables and 3) the establishment of the optimization and decision-making model by applying NSGA-II and TOPSIS methods. By applying this three-stage decision-making model, this paper first proposes cost-effective passive design solutions for office buildings throughout the Hot Summer and Cold Winter climate zone. Finally, an office building in Shanghai was chosen as a case study to demonstrate the practical implementation of the proposed solutions through a post-occupancy evaluation with a two-year energy auditing and thermal comfort survey. It is evident that the proposed solutions provide support for the new low energy building design guide for office buildings along with necessary revisions to the existing standards for the Hot Summer and Cold Winter climate zone in China. [ABSTRACT FROM AUTHOR]

Based on household-level survey data collected from Qinghai Province of China, we estimated the greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. • We used empirical data from rural households in Qinghai, China. • This paper indicates the reliance of local energy consumption on non-commercial energy. • We estimate greenhouse gas and pollutant emissions resulting from solid-fuel combustion. • We compare indoor pollutant emissions from pastoral, agropastoral, and agricultural zones spatially. • This paper provides policy recommendations for energy transition towards clean energy. Energy consumption in the household sector has become an important issue in China's energy consumption and an important unit of China's clean energy transformation. Currently, the potential air pollution, carbon emissions and health risks caused by energy consumption in many areas cannot be ignored, and refined and regionalized index-based research data necessary to support decision making are lacking. Based on household-level survey data collected from Qinghai Province, China, we estimated greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. These findings highlight the need to integrate household energy policies with rural development to enable a complete transition towards cleaner fuels. [ABSTRACT FROM AUTHOR]

Although China's heat metering technology has developed rapidly in recent years, the improvement demonstrates an unbalance in different provinces. It is of great significance to outlook application and sustainability of heat metering technology in various regions technically. Taking the sustainability of heat metering technology as research object, the author establishes a sustainable evaluation model in this paper. Factors in the evaluation model are assigned through a main questionnaire and actual application of typical projects. A pecking-order contrast method is adopted to determine weights of factors in the evaluation model, correspondingly sustainable development of heat metering in various locations is assessed. Sustainability scores in three regions (Northeast, Northwest and North China) are obtained via evaluation model. The model owns high accuracy compared with results of heat metering work assessment by the Ministry of Housing and Urban-Rural Development (MOHURD). The heat metering in the three regions score 60, 62 and 75, respectively, implying that the sustainability in the northeast and northwest is unsatisfactory but in north is somehow better. It is suggested that envelope heat insulation should be increased in the northeast region, while policy support and heat metering technology ought to be enhanced in the northwest. [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 building energy codes (CBEC) have been introduced for over two decades but little has been publicized in literature. LEED on the contrary is the most publicized building environmental assessment scheme. To enable better understanding of the compliance standards of CBEC, this paper presents the energy performance assessment results (represented by energy and energy cost savings) of three office buildings in China (one in Beijing and two in Shanghai) using the current versions of CBEC and LEED. The energy and energy cost savings of the three buildings were predicted based on hour-by-hour simulations using the weather data and energy tariffs of Beijing and Shanghai where the three studied buildings are located, and their actual building and system characteristics. The study revealed that LEED in general sets more stringent requirements than CBEC in indoor design conditions, building envelope characteristics and air-conditioning system features. Amongst various building end uses, energy use for air-conditioning was found dominating the assessment results, and the use of energy efficient measures not forming part of the baseline criteria, could lead to 2 to 5% reduction in the overall building energy use. The two schemes were benchmarked against BEAM Plus and their weaknesses were also unveiled. [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]

A large part of energy consumption in homes, offices and commercial spaces is related to Heating, Ventilation and Air-conditioning (HVAC) devices. The effective parameter on the consumption of HVAC systems is internal heat gains that arise from occupants, electric equipment and lighting. In order to reduce the energy consumption of these systems, internal heat gains should be predicted accurately. Since there are few investigations performed on the prediction of internal heat gains, in this paper, three predictive models, namely multiple regression model, Levenberg–Marquardt back-propagation (LM-BP) model and similar days method based on combined weights, have been deployed. By assessing the influential factors on internal heat gains, fundamental theories, structures, equations and parameters of these models are thoroughly proposed. To examine the prediction techniques, an office building in China was considered. It was found that all the proposed models have high accuracy; however, the LM-BP neural network showed the most precision among other models with RMSE = 15.59, MAE = 10.16 and MAPE = 6.35. This model had a higher agreement with the actual internal heat gains compared to the predetermined working programs in the ASHRAE standard 90.1. The proposed models used in this study can lead to providing a theoretical base for scholars and engineers to improve the predictive control of HVAC systems, which plays an important role in enhancing thermal comfort, saving energy of residential buildings. [ABSTRACT FROM AUTHOR]

• A net zero energy wooden structure building in severe cold zone was designed in severe cold zone. • A new type of water-passing wall was designed and applied in the wooden structure building. • Renewable energy systems are adopted to pursue net zero energy consumption for wooden structured buildings in severe cold areas. • Study on the operational performance of wooden structure building. • Evaluated the energy criteria and economy of the wooden structure building. At present, there is no lack of research on net zero energy buildings (nZEB) in China, and most of the research on "nZEB" focuses on buildings using traditional building materials like rebar concrete, brick, etc. In this paper, we take a wooden structure residential building in the severe cold zone as the research object, design a new type of water-passing wooden structure wall, and explore how to achieve net zero energy consumption through appropriate methods in the design stage. During the operation of the wooden structure building throughout the year, the solar photovoltaic (PV) system provides electricity to the building. In the heating season, we will supply groundwater or shallow geothermal water into the water pipes in the wall, and the solar thermal system provides hot water for heating. According to the whole year operation of the wooden structure building, the indoor environment meets the requirements of comfort standards, and the designed envelope structure of the wooden structure building has an excellent thermal performance. The energy consumption was reduced by 62.9% compared with energy-saving buildings without water-passing walls. The electricity generation capacity of the solar PV system is more than the actual electricity consumption of the building, the energy criteria are met the relevant requirements of the net zero energy building, and its economy is also evaluated. [ABSTRACT FROM AUTHOR]

• A dual-objective optimization method from the perspective of designer and user. • Life-cycle energy and economy optimization for building Design Period based on HypE. • Use Low-E insulating glass, rotate the building 18°counterclockwise are beneficial. • Life cycle energy consumption and economy of the case are reduced by more than 15%. Multi-objective optimization of building life cycle energy consumption and cost is very essential for guiding design quantitatively. However, previous studies paid more attention to the potential effect of building energy saving and cost reduction based on design parameters from the perspective of designers, but ignored the potential brought by the willingness of users during operation stage. Therefore, this paper proposes a dual-objective optimization method based on the HypE algorithm, which takes into account users' energy saving intentions in order to maximize the potential of building life cycle energy saving and cost reduction. The application premise of this method is to establish energy and cost calculation model of building life cycle. The method was applied to the design of a small office building in Xi'an city of China, and the scheme were optimized by adjusting 7 design parameters and 2 parameters (cooling and heating temperature) related to the energy saving willingness of the users. The results show that the proposed method can reduce the energy consumption by 15.1%-18.8% and the cost by 2.2%-10.1% during life cycle. The results will continue to be reduced by up to 6.5% and 12.02% if the potential of uers' willingness to save energy continues to be realized. It is proved that the proposed method contributes to the comprehensive evaluation of energy saving and economic effects of architectural design during its life cycle and provides effective theoretical guidance and practical tools for architectural design and optimization. [ABSTRACT FROM AUTHOR]

• This method integrates uncertainty analysis and cluster analysis methods. • Proposed novel zoning indicators are statistically significant. • Moves from traditional weather-based approaches to a performance-based approach. • Robust tool to tackle complex relation between climate and building energy efficiency. • Provide evidence for the rationality of decision making in energy policy. Climatic zoning is an important tool in building energy policy and regulations, smaller and more homogeneous climate zones could help enhance the rationality of energy policymaking. In most countries, climate zoning is based on simplified climate models, and it is difficult to accurately represent the energy demand characteristics of buildings. Therefore, this paper proposes a novel climate subdivision method that tackles the complex relations between climate and building energy-efficient, which move from traditional weather-based approaches to a performance-based approach. Integrate the uncertainty analysis method and the building dynamic performance simulation to extract a novel statistically significant index as the basis for classification. The K -means clustering method and discriminant analysis method are used to obtain and verify the clustering results, respectively. Furthermore, the comparison with clustering results based on degree days confirms the superiority of the new method proposed in this paper in identifying building energy demand. The method is applied to the cold climate zone of China as a showcase. The results show significant differences in building energy demand and the order of key features affecting building performance between each region in the climatic zones. The zone can be further sub-divided into four groups considering the climate factor and building feature uncertainty, and clustering results have been verified by several evaluation indicators. [ABSTRACT FROM AUTHOR]

• Sunken courtyards reduce the household energy consumption of farmers nowadays. • Policy guidance and building conditions are the main factors that affect decision-making of living modes. • Village collective and individual decisions affect the energy consumption level of the whole village system. • Vernacular architecture is the local solution of rural energy-efficient development. Vernacular architecture has been widely concerned in recent years because of its energy-efficient and environmental adaptability characteristics, and is considered as a potential method to reduce rural energy consumption and an important cultural heritage. However, under the rural modernization and urbanization, vernacular architecture is in danger of disappearing. This paper focuses on the sunken courtyard, a typical vernacular architecture that utilizes underground space, carries out field investigation and questionnaire survey in villages of Shanzhou District, China. It is found that local residents adopt a variety of spatial utilization modes for sunken courtyards, and the structural equation model is further applied to analyse the decision-making process of farmers. The result is as follows: First, the utilization of sunken courtyards still reduces the household energy consumption; Second, policy guidance (weight coefficient is 0.57) and objective building conditions (weight coefficient is 0.25) are the main factors that affect farmers' decision-making; Third, village collective and individual decisions affect the energy consumption level of the whole village system. Finally, the formulation of rural development policies should fully consider the relationship between residents, buildings and village systems, so as to form unique local solutions. This study provides insights for the development of future architectural heritage conservation and rural renewal strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] The rapid development of urbanization has created high demand for central heating systems. This trend has led to an increase in energy consumption for central heating, which has made China's energy-saving transformation extremely difficult. However, the channel by which urbanization impacts and the future trends of energy consumption for central heating are still unclear. Therefore, this study employs the Logarithmic Mean Divisia Index (LMDI) method to decompose the effect of urbanization on changes in energy consumption for central heating during 2001–2019 in China. We investigate the contribution of urbanization from demographic, economic and spatial perspectives. Additionally, a scenario analysis is used to explore trends in energy consumption for central heating in different projected urbanization scenarios. The results show that urbanization has a positive impact on energy consumption for central heating, particularly in underdeveloped regions. Demographic urbanization has the strongest positive effect on energy consumption for central heating, followed by spatial urbanization and then economic urbanization. Compared with the expansion of area and economic development, population agglomeration will bring more energy consumption for central heating. The forecasting results indicate that energy consumption for central heating will reach 176–189 Mtce in 2030, which is approximately 1.4 times the current level. This work quantifies the energy consumption for central heating in the future under urbanization. The policy recommendations given at the end of the paper will provide a reference for the formulation of energy consumption for central heating. [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]

[Display omitted] • Coal combustion, ASHP, solar heating, gas furnace and electric heating are compared. • Thermal comfort, economic, energy consumption and environmental benefit are evaluated. • Different PMV-PPD are set, and the design thermal index is amended. • The optimal heating mode of rural buildings in cold areas is found. In recent years, space heating modes are diversified. In the early stage of space heating design, we should reasonably evaluate and optimize the heating mode in order to get a better heating effect. In the past, the evaluation of different heating modes was mostly single evaluation. In this paper, the thermal comfort, economic, energy consumption and environmental benefit are comprehensively evaluated. Four heating modes in the "Coal to electricity" project of China are compared with coal combustion. The modes are ASHP (Air Source Heat Pump), solar heating, gas furnace and electric heating. Based on PMV-PPD, a more reasonable design thermal index of 35.18 W/m2 is obtained. The matched capacity and operation of heating system are optimized. The results show that ASHP combined with floor radiation heating is the best space heating mode in cold areas of China. The comprehensive rate of the four evaluations is 89.64%, and its thermal comfort is the best. For a 120 m2 house in Lanzhou, after the transformation of traditional coal burning heating mode, the static payback period is 6.9 years. The actual energy consumption reduction of society is 2,769 kg/year. The reduction of CO 2 emissions is 4,014 kg/year. [ABSTRACT FROM AUTHOR]

• 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]

• The energy consumption of 38 Chinese district heating systems was investigated and compared. • Method to break down the consumption and evaluate the operational problems was presented. • Field measurements were conducted to evaluate problems leading to high energy consumption. • Overheating was responsible for 23% of total heat consumption. • Resistance, operation flow, and pump efficiency were three major problems in distribution networks. Worldwide, China has the largest district heating (DH) area and is also the fastest growing country. This paper presents field measurement results for operational energy consumption from 38 DHSs to fill in the gaps in understanding of the current operational issues of the district heating system (DHS). The average heat consumption during the heating period was 98.6 kWh/m2 and the monthly average electricity consumption for circulating pumps in the primary and secondary networks was 0.27 kWh/(m2 × month) and 0.29 kWh/(m2 × month), respectively. Thereafter, a systematic method for breaking down the energy consumption and quantitatively evaluating the underlying problems is presented. Based on several detailed measurements conducted in typical heat-exchange substations (HESs), it was found that overheating was the most prominent problem in energy-efficient buildings, constituting 23% of the total heat consumption. Another problem encountered was heat loss through pipes, which constituted approximately 5%–10% of the total heat consumption and was highly dependent on the actual conditions. In distribution networks, problems such as high resistance, high operational flow, and low pump efficiency were also identified and analyzed. Finally, practical energy-efficiency suggestions and future potential targets for the Chinese DHS are discussed from both a design and operational perspective. [ABSTRACT FROM AUTHOR]

In the context of residential energy consumption, the top-down approach and bottom-up approach have been developed to model and predict residential energy demand, and the bottom-up engineering model is a promising choice and an effective tool for urban planners and policymakers. However, unlike the existing building stock databases in some developed countries or regions, China's Pearl River Delta (PRD) region lacks such building databases. Thus, the study established a database of 120 residential districts in the PRD region, and developed typical models through the data of the collection, quantification and classification. In this paper, three typical residential district models have been defined, which was a supplement to previously develop seven typical residential building models. Moreover, four common family patterns in the PRD region were determined by literature research, the corresponding schedules and basic settings were developed subsequently for them. Finally, the simulations of the energy consumption of the three residential districts were conducted, whose energy consumption intensities were 28.43 kWh/m2a, 28.41 kWh/m2a and 28.24 kWh/m2a, respectively. The results of the simulation are similar to the results of the actual energy audit, which is considered that the typical residential buildings are representative yet simple-to-use energy model. [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]