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As most promoted solution of climate change, green buildings become more popular and widely promoted in China recently. This paper compared the carbon emissions of green buildings with non-green buildings; therefore, a life cycle carbon emission assessment approach (LCA) was attempted. In the present paper, we have integrated existing database Building Environmental Load Evaluation System (BELES) developed by Tsinghua University and twenty-six real existing buildings (nine residential and seventeen commercial buildings). Buildings located in two major climate zones were selected, namely, zone II and III. Five phases were defined for a whole life cycle of building: Phase 1 Raw Materials, Phase 2 Transportation, Phase 3 Construction, Phase 4 Operation & Maintenance and Phase 5 Demolishment. In each phase, the emissions were calculated separately. It is found that whole life cycle CO 2 (LCCO 2 ) of green buildings are lower than that of non-green buildings, i.e., 10% for residential and 32% for commercial buildings, respectively. For both residential and commercial buildings, Operational & Maintenance phase contributes the majority of emissions in the whole life cycle, about 69.2–89.3%. Moreover, green buildings have slightly higher embodied CO 2 emissions than non-green buildings, but with much lower operational emissions, and this phenomenon is significant in residential buildings. This indicates that the LCCO 2 of green buildings start to match with LCCO 2 of non-green buildings after operating for certain years, which is the turning point. Furthermore, China implemented Standard for Energy Consumption of Buildings in December 2016, which listed two values for energy efficiency in operational phase, which represents requested and optional. It can be expected that the emissions in Operational & Maintenance phase of green buildings will be further reduced in the future. Consequently, in the future, the dynamic flow of turning point of residential buildings will be shifted downwards from existing 14 years found in this paper. [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]

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]

Emission reduction in buildings is essential to combat climate change. However, current strategies failed to balance development and emissions reduction goals. This paper selects a public building in China and simulates its initial energy consumption and carbon emissions. Then it establishes a multi-objective optimization model to explore cost-effective and emission-reduction strategies, considering photovoltaic and ground-source-heat-pump (GSHP) systems. Finally, NSGA-Ⅱ is used to solve, and sensitivity analysis is carried out. Results show that: (1) Energy consumed by the air conditioning system is the largest in January for heating and in July for cooling, validating the accuracy of the energy simulation model. (2) Economic efficiency and emission reduction effect are better when photovoltaic and GSHP systems are implemented simultaneously. (3) Electricity price, initial investment cost, annual solar peak hours, and the proportion of shallow geothermal energy significantly impact carbon emissions and cost. (4) The photovoltaic and power grid substitution ratio will exceed 8% every five years, and all substitutions will be completed in 2050. After adopting the GSHP system, the complete replacement will be advanced to 2045. Setting subsidies significantly shortens the payback period of investment and ensures firms' economic benefits. In summary, using photovoltaic and shallow geothermal energy is conducive to reducing emissions and saving costs in the long term. [ABSTRACT FROM AUTHOR]

This paper presents a micro energy grid to a community and estimates the effect of the urban micro energy grid on the reduction of energy demand and carbon emissions. Micro energy grid enables to share various energy sources generated at local plants and renewable sources for multiple buildings with different energy profiles. A community in China was selected for the implementation of the micro energy grid. A number of key performance indicators(KPIs) were developed to act as a framework for the overall community micro energy grid design. Site-wide strategies were selected to meet the KPIs and minimize the capital cost of the project. Financial analysis on the community micro energy grid model was performed and different scenarios were set up in order to find the optimalconditions for the government incentive, the investment discount rate, system capacity and development (demand) size of the project. It was found that a community in China adopting micro energy grid can achieve 26% carbon emissions reduction and 25% energy consumption savings compared to the conventional building energy systems and its payback period is 51 years with 10% discount rate and a government incentive of $0.052 per kWh. [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]

• 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]

Using energy conservation measures (ECMs) for building retrofit can significantly reduce building operational carbon emissions (BOCEs) and contribute to Chinese carbon neutrality by 2060. This paper involves 11 feasible ECMs for commercial buildings in hot-summer and cold-winter zone, China, and proposes a quick assessment approach to BOCEs reduction. Prototypical models are simulated for ECMs using EnergyPlus and the emission intensity is corrected by the building shape factor and window-to-wall ratio. Based on pre-simulated results, effects on reducing emissions of individual measures and packages of them are studied to develop regression models in SPSS. The results show that decreasing the U-factor of external walls, lighting power density (LPD), or shading coefficient can reduce BOCEs linearly. BOCEs are most sensitive to LPD and using daylighting control can reduce emissions by 5–15%. In addition, increasing the boilers' efficiency reduces emissions linearly, while performance improvement of chillers or heat pumps reduces emissions logarithmically. Furthermore, utilizing variable speed pumps, heat recovery ventilation, and air-side economizers can reduce emissions by 3.8%, 6.6%, and 15.2%, respectively. Finally, significant interactions exist among measures of enhancing glazing U-factor, adding external shading, using energy-saving lamps, and improving cooling/heating system efficiencies. The developed regression models are validated in a retrofit case in Shanghai. Through assessment, the case can reduce BOCEs by 15.9 kgCO 2 /m2, with a reduction rate of 20.8%. Compared with recorded data, the relative error of assessing emission reduction is −13.0% and that of assessing reduction rate is 0.5%, which are acceptable in the decision-making stage of retrofit strategies. [ABSTRACT FROM AUTHOR]

• Build the load uncertainty model of incorporating the annual load growth rate. • Integrate the grid integration level into multi-objective optimization. • Propose the multi-objective two-stage adaptive robust planning method. • Implement the planning method into an industrial park. • Analyze the influence of quantitative parameters on the evaluation indicator. An integrated energy system (IES) is considered as an effective approach to reduce carbon emissions, lower energy supply costs and increase system flexibility. As numerous energy conversion and storage devices with various features have been developed, determining their types and capacity size and optimizing the synergic action of all selected energy devices under load uncertainty have become challenging issues during the planning and designing of a new IES. To address these issues, a load uncertainty model is constructed by integrating the regional equivalent standard building-integrated load prediction method, the robust uncertainty set method and the fuzzy C-means clustering algorithm. Based on this uncertainty model, this paper proposes a planning method that incorporates the fuzzy multi-objective decision and two-stage adaptive robust optimization methods for handling these challenging issues. The multi-objective decision method enables comprehensive optimization based on the system's economic performance, carbon emissions and grid integration level. The two-stage adaptive robust optimization method aims to optimize the single-objective problem transformed by the multi-objective decision method. The planning method is implemented in an industrial park in the Baoding City of China. The influence of load budget uncertainty, annual load growth rate and energy purchase price is then investigated. The results show that the load budget uncertainty and annual load growth rate only affect the optimal capacity size of the selected devices, whereas the energy purchase price influences both the optimal device types and their capacity size. The optimal capacity size remains constant when the load budget uncertainty exceeds 3. This study provides a methodology to select the suitable device types and determine their capacity size for IES under load uncertainty, which will benefit the design of a new IES. [ABSTRACT FROM AUTHOR]