Residential Buildings In China Research Articles

Optimizing passive energy savings in rural self-built houses: Integrating phase change materials across China's climate zones

The energy consumption of rural residential buildings in China is increasing, and the integration of phase change materials (PCMs) has emerged as an effective strategy to mitigate building energy use and carbon emissions. Given China's diverse climate zones and the varying construction forms of rural self-built houses (RSHs), the efficacy of PCM applications varies significantly across regions. This study presents a comprehensive investigation into passive energy savings using PCMs in RSHs across various climate zones. We investigate the energy saving potential and thermal comfort effects of installing PCMs with varying phase change temperatures and thicknesses at different laying positions in representative buildings from each climate zone. The results indicate that the optimal phase change temperatures in different regions closely align with the outdoor average temperatures during the application season. When the optimal phase change temperatures and appropriate thicknesses of PCM are applied, cost-effective energy savings are consistently achieved in building roofing across regions, with the most significant effects observed in the Severe Cold region, where the uncomfortable degree hours reduction rate (φUDH) exceeds 90 %.

The environmental impact of the entire renovation process of urban aged residential buildings in China

The environmental impact of the entire renovation process of urban aged residential buildings in China

Spatio-temporal distribution and peak prediction of energy consumption and carbon emissions of residential buildings in China

With the acceleration of urbanization and the improvement of people's living standards, the carbon emissions of residential buildings (BCE) in China have been increasing, hindering the achievement of carbon peaking and carbon neutrality goals. It has become increasingly urgent and important to analyze and grasp the dynamic trends of BCE. Given the notable regional variations in carbon emissions, it is necessary to delve into the distribution characteristics of BCE and the underlying factors influencing them. First, based on the emission factor method, the energy consumption and carbon emissions calculation models are established. Next, the main influencing factors are obtained by improving Kaya's constant equation. Meanwhile, the GA-PPC-Kmeans model is established to divide BCE into different regions. Then, the STIRPAT-Ridge model is built to predict the peak carbon emissions. Finally, a combination of static and dynamic methods is used to forecast peaks under three scenarios, which are low-carbon (LC) scenario, baseline (BA) scenario, and high-carbon (HC) scenario. The results show that five pivotal factors significantly impact BCE in China, which are energy carbon emission intensity (ECEI), energy intensity (EI), economic density (ED), residential housing level (RHL) and population size(P). Furthermore, BCE is categorized into five distinct regions: low-carbon demonstration area, energy efficiency improvement area, carbon concentration and innovation area, high-carbon optimization area, and carbon poverty development area. Under BA scenario, the peaks for BCE in these regions converge primarily around 2040 and 2045. This study provides a regional research perspective for China's residential buildings to reach the peak of carbon emissions, and serves as a reference for formulating carbon emission reduction plans in different regions.

Refining adaptive models for overheating evaluation: Evidence-driven comparative analysis of residential buildings in China's cold and severe cold regions

China's residential buildings in cold and severe cold regions grapple with unaddressed summer overheating issues owing to the lack of tailored regional standards, necessitating a critical examination through globally recognized thermal comfort benchmarks. In this study, 27 bedrooms and 47 living rooms in 13 representative cities were monitored from May to September in the years 2021–2023 to investigate the summer indoor operative temperature of residential buildings in 5 sub-regions. The accuracy of adaptive models from ASHRAE 55, EN 16798–1, and GB/T 50785 for overheating evaluations was tested using measured data. Further, the Chinese Thermal Comfort Database (CTCD) was expanded in this study to enable the development of a preliminary Summer Residential Adaptive Model (SRAM) specifically designed by considering the distinct characteristics of China's cold and severe cold regions. Analysis of the monitoring results showed that 73.1 % of living rooms and all bedrooms were overheated according to CIBSE TM59. Moreover, the slope of SRAM is 0.40, which is lower than 0.73–0.77 of GB/T 50785 and higher than 0.31 and 0.33 of ASHRAE 55 and EN 16798–1, respectively. Further comparative assessments revealed inconsistencies with actual human sensations of heat. The results of this study highlight the inadequacy of CIBSE TM59 and existing thermal comfort standards in accurately assessing building overheating in China's cold and severe cold regions. To improve evaluation, future research must integrate regional climate modeling, various architectural configurations, and thermal sensation indicators to refine the developed SRAM, thus enabling the establishment of more holistic thermal comfort standards.

Techno-Economic Analysis of a High-Rise Residential Building Adapted to Nearly Zero-Energy Building Standards

Zero-energy buildings have attracted great attention in China. Limited research about typical high-rise, zero-energy residential buildings in China was found. To figure out the potential of zero-energy buildings in northern China, a techno-economic analysis of a typical residential building adapted to the nearly zero energy building (NZEB) standards in the cold region of China was carried out in detail in this paper. Firstly, the feasibility of different building energy efficiency technologies was figured out in the passive design level. Secondly, the annual energy balance of the nearly zero-energy building model was investigated. Finally, detailed economic and environmental analyses were performed. The results show that the energy consumption of space heating and cooling of a typical high-rise, nearly zero-energy building could decrease to 11.1 kWh/(m2·a) in Beijing. The conclusions could provide a reference and design basis for the development of zero-energy residential buildings in northern China in the near future.

FEASIBILITY STUDY OF RETROFITTING ASSESSMENT FRAMEWORK FOR SUSTAINABLE MULTI-STOREY RESIDENTIAL BUILDINGS: A CASE STUDY OF CHINA

The construction industry is one of the primary sources of carbon emissions. In the context of the global response to reduce greenhouse gas emissions and the impacts of climate change,China implements the Carbon Peaking and Carbon Neutralisation policy. The policy vigorously promotes energy conservation and emission reduction in the construction industry, particularly housing. Due to the large stock of existing old multi-storey residential buildings in China, most of which are not energy-saving, and the lack of a sustainable assessment framework to retrofit such buildings, it is deemed essential to analyse the shortcomings of the current assessment standards and frameworks and formulate a better alternative. Therefore, this paper aims to provide the rationale for proposing a sustainability assessment framework for retrofitting old multi-storey residential buildings in China. It first explains the concepts of sustainable development and housing, then combs the current Chinese government’s commitments to sustainable housing agenda. The unsustainable state of this housing type is then reviewed, followed by the issues and gaps in the existing sustainable building assessment standards in China and overseas to justify the necessity of developing a sustainability assessment framework for retrofitting multistorey residential buildings in China. This framework would assist the retrofit of old multistorey residential buildings in reducing energy consumption, improving efficiency and achieving sustainable development. It also contributes to the body of knowledge in sustainable building assessments and helps in the planning and design processes within the public and private sectors related to the construction industry.

A novel quantitative method of heatwave classification for building resilience analysis

More frequent and extreme heatwaves result in an increased risk of overheating in residential buildings. The utilization of heatwave weather files is fundamental in evaluating the thermal resilience of buildings. However, limited studies have focused on quantitative classification methods that consider multiple heatwave characteristics and how buildings respond to different heatwave types. Therefore, this study aims to propose a quantitative method for classifying heatwaves by considering the duration and intensity, while also providing the thresholds for duration and intensity to identify different types of heatwaves. Subsequently, the impacts of different types of heatwaves on indoor overheating was quantified and compared through simulation of indoor thermal environment in three prototype residential buildings in China. The indoor overheating risk was then evaluated based on the indoor overheating degree. The results revealed four types of heatwaves: short and moderate, short and intense, long and moderate, and long and intense. The short and moderate heatwaves represented the majority. While the long and intense heatwaves had the highest influence on indoor overheating risks. Hence, these two types of heatwaves are suggested to be considered in building resilience analysis. The proposed method demonstrated its effectiveness in classifying heatwaves based on the impact on indoor environments.

Gas engine CCHP system optimization: An energy, exergy, economic, and environment analysis and optimization based on developed northern goshawk optimization algorithm

This paper aims to enhance the design and operation of a Combined Cooling, Heating, and Power (CCHP) system utilizing a gas engine as the primary energy source for a residential building in China. An Energy, Exergy, Economic, and Environment (4E) analysis is employed to assess the system's performance and impact based on energy, exergy, economic, and environmental criteria. The effectiveness of the DNGO algorithm is evaluated on a case study site and compared with Northern Goshawk Optimization (NGO) and Genetic Algorithm (GA). The findings demonstrate that the DNGO algorithm identifies the optimal gas engine size of 130 kW. The algorithm's search capabilities are greatly enhanced by this unique blend, surpassing what traditional methods can offer. The DNGO algorithm brings several advantages, including unparalleled energy efficiency, reduced exergy destruction, and a substantial decrease in CO2 emissions. This not only supports environmental sustainability but also aligns with global standards. Economically, the algorithm enhances the performance of the CCHP system, evident through a reduced payback period and increased annual profit. Additionally, the algorithm's rapid convergence rate allows it to reach the optimal solution faster than its counterparts, making it advantageous for time-sensitive applications. Incorporating innovative methods like chaos theory, the DNGO algorithm effectively avoids local optima, enabling a broader search for the best solution. The utilization of Lévy flight further enhances the algorithm's ability to escape local optima and navigate the search space more efficiently. Additionally, swarm intelligence is employed to simulate the collective behavior of decentralized systems, aiding in problem-solving. This research represents a significant advancement in optimization techniques for CCHP systems and offers a fresh perspective to the field of swarm-based optimization algorithms.

Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Under the backdrop of China’s national strategy to achieve carbon neutrality by 2060, efforts are underway across governmental, corporate, societal, and individual sectors to actively explore energy-saving renovations in existing buildings. Given that residential buildings constitute a significant proportion of the total energy consumption throughout the lifecycle of buildings in China, sustainable renovation of residential structures can contribute significantly to implementing China’s carbon emission reduction policies. While there exists a plethora of technological means in the market aimed at improving the energy performance of residential buildings, there still needs to be a more systematic discussion on the framework for sustainable renovation of existing Chinese residential buildings, with knowledge dissemination still needing to be more cohesive. In this context, this paper provides a comprehensive review of the field, utilizing bibliometric methods. Through a systematic review of selected peer-reviewed literature from the Web of Science and Scopus databases, the study focuses on the sustainable renovation of existing Chinese residential buildings, categorizing the process into three main stages: sustainable renovation, building performance simulation and suitability assessment. The paper also reviews the research methods adopted by previous researchers in the renovation, simulation and assessment stages, considering various optimization algorithms, variables, objectives, and software tools. Subsequently, the paper synthesizes a research framework comprising these three stages combined for different research objectives, aiming to assist policymakers, designers, and researchers in gaining a comprehensive understanding of the implementation status of sustainable renovation in existing Chinese residential buildings, identifying barriers to implementation, and formulating more efficient renovation policies and strategies for the future.

Predictive models of embodied carbon emissions in building design phases: Machine learning approaches based on residential buildings in China

As one of the major architectural forms, residential building construction consumes considerable resources, and it has been regarded as a crucial factor for the implementation of carbon peaking and neutrality targets. Estimation of carbon emissions is essential for making informed decisions regarding building design and carbon reduction measures. Some studies have established predictive models for building operational carbon emissions. However, there are relatively few studies concerning the prediction of embodied carbon emissions. This study established a dataset containing 850 residential building samples. Based on the trade-offs and combinations of different explanatory variables, including building features and material use, this study developed two-phase models. These models, incorporating six scenarios, predicted embodied carbon intensities using twelve machine learning algorithms. For the planning design phase, an extremely randomized tree model using the building height, structural form, seismic fortification intensity, delivery form, geographical region, and material cost as inputs was favored considering R2 as 0.821 on the testing dataset. For the preliminary design phase, an extreme gradient boosting model using both building features and material intensities provided superior performance with R2 and MAPE values of 0.917 and 0.038, respectively. The optimal models and relevant feature importance analysis can be helpful for efficiently predicting embodied carbon emissions, and therefore, facilitate low-carbon designs.

Performance Analysis of Application of BIM Technology and Two-Way Progressive Optimization Algorithm in Energy-Saving Design of Residential Buildings Based on BIM Technology

The current residential energy-saving design is lagging behind, and lack of systematic design methods and scientific technical means seriously restricts process of improving quality of residential buildings in China. With development and application of digital information technology in construction field, BIM technology has brought new opportunities construction industry, and building performance data has become information basis for scientific promotion of energy conservation. This paper uses BIM technology as a platform to establish an information base of common building materials and components in Chongqing through literature research, field studies, summarization, and application practice, and to help architects make wise decisions at early design stage by using "one-click" scheme comparison and design evaluation to avoid a large number of potential energy consumption problems at a later stage, It greatly improves energy efficiency and design quality of buildings.

Enhancing domestic hot water energy efficiency in High-Rise residential buildings through interconnected and sharing mode

Residential buildings in China are consuming over 20 % of their operating energy on domestic hot water (DHW), a percentage that has been increasing in recent years. The use of energy-efficient water heaters is a direct solution to reduce DHW energy consumption, but high costs and installation requirements often deter households from adopting them. This issue is particularly prevalent in high-rise residential buildings, resulting in a low adoption rate of energy-efficient water heaters in China's high-rise residential sector. To address this challenge, this study proposes a DHW interconnected and sharing mode as a novel approach to enhance DHW energy efficiency in high-rise residential buildings. A dynamic performance calculation model based on the China Energy Efficiency Label (CEEL) for various types of water heaters was developed to evaluate the energy efficiency of this mode. The total energy consumption, carbon emissions, and energy costs of the building were assessed under both decentralized mode and interconnected and sharing mode. The findings indicate that implementing the interconnected and sharing mode can significantly decrease the annual total energy consumption, carbon emissions, and energy costs of DHW. Among the two operational strategies examined (economic optimal and environmental optimal), the economic optimal strategy is more suitable for China's current energy landscape. Under the economic optimal strategy, the annual total energy consumption, carbon emissions, and energy costs of DHW in the target building are reduced by 41.58 %, 27.97 %, and 34.87%, respectively.

Statistical characteristics and scenario analysis of embodied carbon emissions of multi-story residential buildings in China

Residential buildings are major contributors to carbon emissions from the building and construction industry. Although previous studies have comprehensively investigated the methods for embodied carbon assessment and proposed measures for carbon reduction, it remains challenging to screen the features and influencing factors of embodied carbon intensities from a statistical perspective. This study explored the characteristics of embodied carbon emissions based on 438 multi-story residential building samples. The influences of building features, such as the number of floors, number of basements, structural form, seismic design requirement, delivery type, and building area, were analyzed using clustering and significance tests. The average embodied carbon intensity was evaluated as 467.6 kg CO2e/m2 and relevant coefficient of variation was approximately 20 %. Further discussion on building material weight, cost, and embodied carbon intensities indicated that a simplified system boundary considering 95 % thresholds of both weight and cost can provide satisfactory results for embodied carbon assessment with relative errors below 3 %. Moreover, three linear models were proposed for predicting embodied carbon intensities. The results showed that the carbon intensities can be predicted based on five types of primary materials with good accuracy. The proposed system boundary, predictive models, and identified characteristics have practical applications for assessing, estimating, and reducing embodied carbon. Accordingly, it is possible to facilitate low-carbon design of multi-story residential buildings.

Multi-objective optimization of residential building energy consumption, daylighting, and thermal comfort based on BO-XGBoost-NSGA-II

The energy consumption, daylighting, and thermal comfort of buildings directly affect the three key goals of residents. However, there is little research on the optimization of energy consumption, daylighting, and thermal comfort in residential buildings in China. Therefore, this study proposes an optimization framework that combines Bayesian optimization with extreme gradient boosting trees (BO-XGBoost) and non-dominated genetic algorithm-II (NSGA-II) to study the multi-objective optimization of residential building performance. This paper first uses Grasshopper to simulate and obtain a dataset through Latin hypercube sampling (LHS). BO-XGBoost is used to establish the regression relationship between building envelope design parameters and residential building performance. Then, the obtained regression model is used as the fitness function of NSGA-II to get the Pareto optimal solution set. Finally, the ideal point method is used to obtain the optimal combination of building envelope structure parameters for residential buildings. Taking a residential building in a hot summer and cold winter area as an example, the effectiveness of this method is verified. The results show that (1) BO-XGBoost has excellent predictive performance, with R2 values of 0.997, 0.960, and 0.994 for energy consumption, thermal comfort, and daylighting, respectively. (2) The proposed BO-XGBoost-NSGA-II can effectively achieve multi-objective optimization. Compared with the initial scheme of the case building, energy consumption is reduced by 44.1%, thermal comfort index is reduced by 10.9%, and daylighting performance is improved by 1.7%. Therefore, the proposed method can effectively optimize the performance goals of residential buildings and provide practical ideas for similar problems.

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.

Reducing Carbon Emissions from Prefabricated Decoration: A Case Study of Residential Buildings in China

Since decoration is an essential part of buildings, the carbon emissions generated by decoration work should not be ignored. In recent years, prefabricated decoration has attracted much attention as efforts are made to pursue green, low-carbon, and waste-reducing buildings. However, research on carbon emissions assessment of prefabricated buildings has focused mainly on the structural aspect of prefabricated buildings, with few studies having considered prefabricated decoration. This study therefore focuses on assessing the carbon emissions of prefabricated decoration from the life cycle perspective of a case study residential building and explores the potential for reducing carbon emissions by decorating buildings with prefabricated components. The results show that using prefabricated decoration in the case study building reduced carbon emissions by 29.08% at the building material production stage compared to traditional decoration, and using an optimized design of prefabricated decoration, the building’s energy consumption over its design life could reduce carbon emissions by 1046 kgCO2/m2. These findings demonstrate the benefits of prefabrication decoration for reducing carbon emissions. This study provides decoration companies with robust data and insights to guide future decisions and practices, helping to transform and achieve the carbon neutrality goal for the building decoration industry.

Photovoltaic technology in rural residential buildings in China: a comprehensive review on applications, development and its benefits

ABSTRACT China’s rural residential photovoltaic system has been greatly developed in recent years. However, most existing researches, are difficult to reflect the real development situation of the whole system. This study systematically sorts out the results in related fields through the literature review, aiming to clarify the current situation of applications and benefits of photovoltaic technology. The results show that currently the photovoltaic power generation technology is relatively mature and widely applied, and passive photovoltaic technology can play a greater role in reducing energy consumption in rural residential buildings in China. However, the development of photothermal and photovoltaic combined with other energy technologies, as well as the integration between photovoltaic technology and buildings are relatively lagging behind. Besides, the life cycle analysis and evaluation of photovoltaic system has not been established. In view of opportunities and challenges, this study prospects two future development directions. Firstly, the system coupling of photovoltaic technology should be strengthened, especially between the joint supply subsystems, between the active and passive technologies, and between photovoltaic technology and buildings. Secondly, the rationality of photovoltaic technology evaluation should be ensured, particularly to cover the three aspects of economy, ecology and society on the whole life cycle dimension.

Natural Ventilation Potential of Residential Buildings in China Considering the Combined Effect of Indoor and Outdoor Air Pollution

With its rapid economic development, China has had to confront the serious issues of high energy consumption and air pollution. Natural ventilation is regarded as an effective method to reduce building energy consumption, but it is largely influenced by indoor and outdoor air pollution. However, most of the previous studies estimating natural ventilation potential (NVP) in China do not consider air pollution. This research estimated the NVP for residential buildings in major cities from four climate regions in China (Guangzhou, Chengdu, Shanghai, Beijing, and Shenyang) while considering the combined effect of indoor and outdoor air pollution. We compared the yearly NVP in three different scenarios, namely without considering air pollution, only considering outdoor air pollution, and considering both outdoor and indoor air pollution. The results show that Guangzhou had the highest yearly NVP, followed by Shanghai, Beijing, Shenyang, and Chengdu. The impact of air pollution could reduce the annual NVP in China by 78–95%. In addition, the main factors causing a low NVP differed between the four cities. The key factors for Chengdu and Guangzhou were natural ventilation flow rate and indoor air pollution, respectively. Beijing and Shenyang were mostly influenced by outdoor air pollution. Shanghai had two main factors with similar influence degrees, namely outdoor air pollution and indoor air pollution. The findings of this study will guide architects and policymakers in better forming natural ventilation strategies.

Spatial-temporal differences and convergence analysis of residential building carbon emission efficiency in China.

Data indicate that carbon dioxide emissions from residential buildings in China constitute 60% of the country's total, making carbon reduction efforts in residential construction crucial for achieving dual carbon goals. From the perspective of eight major economic regions, this paper selects energy consumption, per capita residential area, and residential population as input indicators, per capita disposable income as the output indicator, and carbon dioxide emissions as the undesired output indicator. It employs the super-efficiency model based on the directional distance (super-DDF) function and the Malmquist-Luenberger (ML) index to measure the static and dynamic carbon emission efficiencies of residential buildings (RBCEE) during their operational phase from 2010 to 2020. After analyzing the differences and equity in RBCEE among regions using the Theil index and Gini coefficient, the σ-convergence, absolute β-convergence, and conditional β-convergence methods are utilized to explore the changing trends of RBCEE across the eight major economic regions. Results show that the static RBCEE in China is at a medium level; dynamic efficiency has improved across all eight regions, though at varying rates; overall, RBCEE exhibits poor equity and significant differences, with intra-group differences being a major cause. In terms of convergence, all eight economic regions display significant absolute β-convergence and conditional β-convergence. Finally, based on the research findings, this paper proposes corresponding emission reduction recommendations for the eight major economic regions.

Evaluating Energy Efficiency Potential in Residential Buildings in China’s Hot Summer and Cold Winter Zones

Evaluating Energy Efficiency Potential in Residential Buildings in China’s Hot Summer and Cold Winter Zones