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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]

[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]

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]

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]

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]

• 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]

• 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]