Office Buildings In China Research Articles

Analysis of carbon emission characteristics and establishment of prediction models for residential and office buildings in China

Intensifying environmental issues make carbon reduction crucial, especially in the construction industry. Embodied carbon emissions (ECE) in buildings characteristically involve concentrated, intensive emissions over a short period. Implementing energy-saving and carbon-reducing technologies has raised ECE rates. Therefore, analyzing carbon emission (CE) characteristics during the production and construction phases is necessary. Currently, essential data on ECE is lacking, the calculation methods are complex, and ECE's characteristics and influential factors in residential and office buildings remain unclear. Moreover, there is a lack of prediction models for ECE in the construction phase that apply to current construction methods and CE factors. The research on prediction models for ECE has primarily focused on the production phase but has paid little attention to the contribution of non-structural materials to embodied carbon (EC). In this study, reinforced concrete residential and office buildings in hot summer and cold winter regions (located in the southeast part of mainland China, with a subtropical monsoon climate) were considered typical types, and the CE characteristics of two main phases, the production and construction phases, were analyzed. Based on critical features, such as the number of floors and the basement, prediction models for ECE in residential and office buildings were established at the design stage. The models were validated with mean absolute percentage error (MAPE) values below 4%, and coefficient of variation (root mean square error) (CV [RMSE]) values less than 0.02. The prediction models enabled a rapid estimation of ECE, encouraging designers to consider EC in the early design stages.

Multi-objective integrated optimization of geothermal heating system with energy storage using digital twin technology

Heat energy storage technology plays a significant role in energy systems, and the various technological solutions brought about by digitalization are especially valuable in the field of energy storage. This article proposes an innovative model based on digital twin technology to solve the supply–demand mismatch problem in geothermal heating systems. This model achieves multi-objective optimization of comprehensive cost, geothermal energy utilization rate, and carbon emission by constructing a heat storage geothermal heating system. Digital twin technology integrates data and information models of public buildings and facilitates their sharing and transmission throughout the entire lifecycle of the geothermal heating system. Initially, the proposed method employs a machine learning-based approach to accurately predict heating demand. Subsequently, the operation of the heat storage water tank and heat pump units is optimized to resolve difficulties in matching energy supply and demand. Finally, the method takes full advantage of time-of-use electricity pricing policies to reduce costs. The data utilized were collected from an office building in China over a period of six months. Experimental results demonstrate that: (1) In terms of predicting heating demand, the improved neural network proposed in this study achieved a prediction accuracy of 98%, which is a 10% improvement over comparative algorithms. Additionally, the experimental comparison of four types of errors showed that the machine learning method proposed had smaller errors across the board. (2) The method realized collaborative multi-objective optimization, and in five scenarios, the comprehensive performance index increased by up to 38.03% compared to the benchmark system. This indicates that intelligent technology is an effective means of enhancing the energy sustainability of geothermal heating systems, and the use of geothermal energy as a clean energy source effectively addresses issues related to the storage, utilization, management, and energy conservation of buildings.

Analysis of carbon emission differences between Chinese and Japanese buildings based on qualitative and quantitative comparisons

As the world's largest carbon emitter, China's building-related carbon emissions contributed to 50.9 % of the country's total carbon emissions in 2020, making it an important area for carbon reduction. In contrast, Japan, one of the world's most energy-efficient nations, has already achieved carbon peaking. To further clarify the current status of China's building carbon emissions and explore a reasonable path for reducing them, this study applied life cycle assessment to analyze the differences in carbon emissions from buildings in China and Japan. Firstly, the impact of five factors (climate environment, building structure, energy structure, population and economy) on the carbon emissions of buildings was assessed qualitatively. Secondly, example calculation and statistical analysis were used to quantitatively compare the carbon emissions of office buildings in China and Japan at the embodied carbon emission, operation, and demolition stages. In the example calculation, the total carbon emissions of the Chinese case are smaller than those of Japan, with the embodied carbon emissions, operation, and demolition carbon emissions are 1.23 times, 0.8 times, and 0.89 times higher than those of Japan respectively. And the statistical results show that the average value of carbon emissions in the Chinese case is larger than that of Japan, and the embodied carbon emissions, operation, and demolition carbon emissions are 1.54 times, 1.29 times, and 2.46 times of Japan respectively. The operation phase contributes 70 % of the difference in carbon emissions, with the nuclear shutdown leading to fluctuations in the carbon emission factor of electricity being the key to the opposite conclusion of the two comparisons. In addition, China has made a lot of efforts to save energy and develop clean energy, and Japan's operation energy consumption is 1.2–2.9 times higher than China's. Finally, recommendations are made in terms of energy saving, carbon reduction, and public awareness.

Economic optimization of exterior wall insulation in Chinese office buildings by coupling artificial neural network and genetic algorithm

Envelope insulation is an essential measure to reduce building energy consumption and is the focus of many building energy codes. In China, the current standard (GB 55015-2021) only specified limit values for the thermal conductivity (U) of the exterior walls, and it ignored variations in building characteristics and internal parameters. Therefore, it is difficult for architects to quickly determine the exterior wall U-value in building design and retrofit. To address this issue, the exterior wall U-values of office buildings in China were economically optimized by TRNSYS, ANN, and GA. To begin with, the effect of enhancing exterior wall insulation on the heating and cooling energy consumption of office buildings was investigated by TRNSYS software, taking into account variations in building characteristics. Moreover, the exterior wall U-values of office buildings were optimized by coupling ANN and GA. The results showed that the design values of the GB 55015-2021 did not achieve the optimal results in China, and the most economical exterior wall U-value was 0.24 W/(m2·K) in Harbin, 0.24 W/(m2·K) in Beijing, 0.42 W/(m2·K) in Changsha, 1.82 W/(m2·K) in Guangzhou, 0.66 W/(m2·K) in Kunming. Compared with the pre-optimization, the annual life cycle cost of building heating and cooling reduced by 0.96 % in Harbin, 2.07 % in Beijing, 1.44 % in Changsha, 1.68 % in Guangzhou, and 7.37 % in Kunming. In addition, variations in building parameters should be considered in the design phase of new buildings or in the renovation of old buildings, such as internal heat gain, which may lead to different optimal results.

Characteristics and Reasons of Manual Shade Use in a Green Office Building: A Questionnaire Based Study

The manual operation of manual shades plays a significant role in actual building performance. The characteristics of the use of shade and the reasons behind it in a green office building in China have been investigated in this paper. A questionnaire survey with 23 questions was designed and a total of 146 occupants in an office building were invited to take part in the survey. Statistical tests and approaches including non-parametric correlation, cross-tabulation, correspondence analysis and clustering were used to identify shade use patterns and their relation with contextual factors. The results show that sitting closer to windows does not necessarily increase shade actions and most shade raise occurs upon arrival and in the morning while most shade-lowering actions appear at noon and in the afternoon. Two and six clusters were revealed by clustering, respectively, for the time of raising and lowering actions. Regarding the relationship between raising and lowering time, three behavior patterns were identified by correspondence analysis. The first group of occupants typically raise the shades upon arrival or in the morning and lower them in the afternoon. The second group has a tendency to lower the shades upon arrival or in the morning and raise them at noon. The last group often raises the shades upon arrival, lowers them at noon or departure, and occasionally raises them again at departure. Given the current situation of light and shade use, daylight, occupancy and shade-based lighting control have the potential for reducing the lighting energy.

Retracted: Simulation Study on Fire Visibility of Typical Floor Planes of Modern Super High-Rise Office Buildings in China

Retracted: Simulation Study on Fire Visibility of Typical Floor Planes of Modern Super High-Rise Office Buildings in China

Impact of outdoor particulate matter 2.5 pollution on natural ventilation energy saving potential in office buildings in China

Natural ventilation improves building energy performance and indoor air quality, but its potential is hindered by outdoor pollution. This paper aims to evaluate the impact of outdoor Particulate Matter 2.5 (PM2.5) pollution on natural ventilation energy saving potential in office buildings in China. Firstly, a typical office building in five representative cities across all climatic regions was designed. Secondly, related weather data were obtained and preprocessed. Thirdly, a computer model was developed under the EnergyPlus environment with smart window ventilation control, space temperature reset using adaptive thermal comfort model, and a validated pollution transportation model that calculates the indoor PM2.5 concentration. The computer model was applied to three air-conditioning systems, i.e., constant air volume (CAV), variable air volume (VAV), and variable refrigerant flow (VRF) with three evaluation indices. The results show that the natural ventilation hours rate with/without considering the outdoor PM2.5 concentration level were 15%–55% and 28%–67%, respectively. Energy savings varied across regions, with mild regions having the highest potential and cold regions having the least. CAV demonstrates the highest energy savings, followed by VAV and VRF, except in Guangzhou where VAV performs the worst. This study contributes to understanding the impact of outdoor pollution on natural ventilation potential and provides practical insights for energy-saving strategies in office buildings. Its originality lies in the evaluation methodology, comprehensive approach, sophisticated computer model, comparative analysis of air-conditioning systems, and practical implications for energy-savings. The research outcomes can guide building facility engineers in implementing ventilation control strategies while maintaining indoor thermal comfort.

Characteristics of office lighting energy consumption and its impact on air conditioning energy consumption

The energy consumption of office buildings has increased sharply since the 21st century with the increasing urbanization coverage. At this stage, the energy consumption of office buildings in China mainly comes from air conditioning and lighting. This paper obtains the regression equation of natural lighting illumination and radiant heat gain under different curtain conditions through experiments and simulations, and gives the theoretical calculation process of curtain regulation of office thermal and light environment and energy consumption. DeST and Ecotect software were used to analyze the thermal and light environment and energy consumption of the office. The results show that setting curtains in the room can effectively improve the indoor thermal light environment, the higher the transmittance of curtains the lower the lighting energy consumption, the higher the number of high temperature hours of natural room temperature and the greater the radiant heat gain. The room with thick curtains has the lowest energy consumption for air conditioning in summer, followed by the room with thin curtains, and the room without curtains has the highest energy consumption for air conditioning. The room without curtains has the lowest energy consumption for artificial lighting, the room with thin curtains has the second lowest, and the room with thick curtains has the highest electricity consumption for artificial lighting. The air conditioning energy consumption accounts for the main building energy consumption, followed by the lighting energy consumption. After setting curtains in the office, the air conditioning energy consumption caused by the solar radiation heat entering the room through the exterior windows is smaller than the lighting energy consumption caused by artificial lighting. Therefore, the installation of internal shading with moderate transmittance and good thermal insulation performance can make the energy saving of lighting and air conditioning energy consumption reach the optimal value.

Siza in China – China in Siza. Observations and Reflections on “The Building on the Water”

ABSTRACT The following article contributes to the inscription of Álvaro Siza and Carlos Castanheira’s Shihlien office building in China (2010–2014) within Siza’s body of work. The Shihlien, also known as the “The Building on the Water,” was an unusual commission for the Portuguese architects, located on a distant site and designed under essentially unknown conditions. The public and critical reception of the building has been shaped by its remote location and private use, as well as by its spectacular form and representation in the media. How, if at all, has China influenced the project and how, reciprocally, has the project influenced China? In analysing Siza and Castanheira’s work, the present article re-employs Kenneth Frampton’s well-known essays from 1983 on Critical Regionalism and enacts two responses to them: 1) on-site observations of the building, together with a response to the experience of the site in terms of the human senses; 2) critical reflections, supported by photographs and notes, directed back at the Critical Regionalist analysis. In conclusion, I argue that the Shihlien both responds to the local context at the geographical, historical, environmental, cultural levels, and offers a statement of continuity in relation to the rest of Siza’s modernist body of works.

Buildings’ internal heat gains prediction using artificial intelligence methods

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.

Indoor humidity levels and associations with reported symptoms in office buildings.

Moderate indoor relative humidity (RH) levels (i.e., 40%-60%) may minimize transmission and viability of some viruses, maximize human immune function, and minimize health risks from mold, yet uncertainties exist about typical RH levels in offices globally and about the potential independent impacts of RH levels on workers' health. To examine this, we leveraged one year of indoor RH measurements (which study participants could view in real time) in 43 office buildings in China, India, Mexico, Thailand, the United Kingdom, and the United States, and corresponding self-report symptom data from 227 office workers in a subset of 32 buildings. In the buildings in this study, 42% of measurements during 9:00 - 17:00 on weekdays were less than 40% RH and 7% exceeded 60% RH. Indoor RH levels tended to be lower in less tropical regions, in winter months, when outdoor RH or temperature was low, and late in the workday. Furthermore, we also found statistically significant evidence that higher indoor RH levels across the range of 14%-70% RH were associated with lower odds of reporting dryness or irritation of the throat and skin among females and unusual fatigue among males in models adjusted for indoor temperature, country, and day of year.

Verifying of the feasibility and energy efficiency of the largest certified passive house office building in China: A three-year performance monitoring study

The high energy efficiency of passive houses (PH) has been widely known and proved over the past thirty years. In its operation phase, it is normally to investigate its energy consumption through the monitoring of building systems, in which the HVAC system is much more complicated than expected. In particular in a complex HVAC concept, it can easily lead to system failures or an increase in large and unnecessary energy consumption, if the HVAC system is not properly commissioned before/after being put into operation. The building systems could be commissioned and optimized based on long-term monitoring results. In the research framework of a PH design and commissioning mode, this article verifies the feasibility of the largest certified PH office building in China, taking into consideration the local climate conditions, the actual energy consumption, and the corresponding indoor environmental comfort, etc. Compared with similar local conventional office buildings, the electricity consumption of this building can be greatly reduced, while indoor environment is still within the comfort range. Its annual energy efficiency can be improved by approximately 69% higher than current Chinese public building standards. The comparison of the monitoring data with the predicted results, also confirms its energy efficiency of this PH building and shows that the HVAC systems commissioning and optimization can bring further energy saving improvement. This case study can provide a good experience for subsequent PH public buildings and a basis for policy makers in China.

Developing a Resource Allocation Approach for Resource-Constrained Construction Operation under Multi-Objective Operation

In the construction industry, it is of great importance for project managers (PM) to consider the resource allocation arrangement problem based on different perspectives. In this situation, the management of resources in construction becomes a challenge. Generally speaking, there are many objectives that need to be optimized in construction that are in conflict with each other, including time, cost, and energy consumption (EC). This paper proposed a multi-objective optimization framework based on the quantum genetic algorithm (QGA) to obtain the best trade-off relationship among these goals. The construction resources allocated in each construction activity would eventually determine its execution time, cost, and EC, and a complexed time-cost-energy consumption trade-off framework of the project is finally generated due to correlations between construction activities. QGA was performed to find the best combination among time, cost, and EC and the optimal scheme of resource arrangement under this state. The construction process is simulated in BIM to check the rationality of this resource allocation mode. An industrial plant office building in China is presented as an example to illustrate the implementation of the proposed model. The results show that the presented method could effectively reduce 7% of cost, 17% of time, and 21% of energy consumption. This developed model is expected to help PMs to solve the problem of multi-objective optimization with limited resource allocation.

A clustering-based climatic zoning method for office buildings in China

Since the influence of building types has not taken into consideration, the current climatic zoning scheme of China may not fully reveal the real energy requirements, especially the annual energy consumption variation of different types of buildings. This study proposes a novel zoning method based on the clustering of building thermal load data of a typical office building. Thermal load simulations were performed under 274 cities’ meteorological conditions across China. Two widely used clustering algorithms: K-Means and Agglomerative Hierarchical Clustering were adopted and compared. Based on the inter-city clustering results, a new zoning map with five distinct zones for building thermal design was developed. To demonstrate the thermal load patterns, especially its dynamic characteristics, three representative cities from the three most densely populated zones were selected for intra-city clustering. The results demonstrate that K-Means method performed better in building thermal design zoning and thermal load pattern analysis, and the optimal thermal zone number is 5. The present zoning method could be applied to other building types and promotes an improvement of the existing zoning strategy. It benefits not only architects, but also building operators and policy makers for energy efficiency design and even green urban design.

Simulation Study on Fire Visibility of Typical Floor Planes of Modern Super High-Rise Office Buildings in China

With the development of office forms, the space form of super high-rise office buildings changed from the unitary efficient office space to a complex space that integrated office, communication, and experience, which also diversified the design of typical floors in the office zone. However, from the perspective of fire prevention, the placement of shared space changed the form of the plane in typical floors in the office zone, affecting the smoke spreading of fire and paths of personnel evacuation. Hence, the subject on the planar relationship among high-rise office buildings based on fire prevention analysis, which optimizes space design, is worthy of discussion. After collecting many cases of super high-rise office buildings in China, this study categorized them into six typical planes and adopted the software PyroSim for comparative simulation of the smoke spreading of fire. By comparing the visibility of different zones in fires, this study analyzed the effects of the area of the office zone, the location of the atrium, and the form of the plane on the fire visibility on the typical floor and put forth the key factors that influence fire visibility, thus optimizing the plane design of the typical floor of super high-rise buildings. The findings show that in the six fire scenes, the area of the office zone is between 1136m2 and 1736m2. The peak of duration for visibility decline at 1.5 m appeared in Scene 3. Its office zone is 1536m2, and the duration of visibility decline is greater than 1000 s. In other fire scenes, the duration of visibility decline is less than 300 s. By comparing the plane arrangement features of the fire scenes, the paper concludes that in a given fire scene, establishing an atrium in the office zone, expanding the length of the adjacent edge between the atrium and the office zone, and building an evacuation corridor between the atrium and the core tube can greatly extend the effective evacuation time. This can serve as reference for the plane design of super high-rise office buildings.

Effect of roof and ceiling configuration on energy performance of a metamaterial-based cool roof for low-rise office building in China

Cool roofs with higher solar reflectance and emittance can effectively reduce building energy consumption. However, it is still limited to use at night on account of the development of roof materials during the past decades. The newly proposed metamaterial-based cool roof (MCR) greatly improves the possibility of the radiative cooling in the daytime. To study the influence of MCR on the energy consumption for the office building, a small single-floor office was adopted to analyse the cooling performance of MCR by using EnergyPlus. In this study, the optimization analysis was conducted based on the proposed dimensionless thermal resistance ( θRTR) and roof pitch (Δ). Then the annual electricity saving potential of the office building with MCR was evaluated in details based on the selected cities from all five climate zones in China. The results show that more annual electricity saving can be achieved under the optimized values of θR7 = 1.53 and Δ = 20°. Furthermore, more than 15.7% of annual cooling electricity saving can be achieved while the optimized θRTR and Δ are applied.

Operation and performance of VRF systems: Mining a large-scale dataset

The energy consumption of air-conditioning systems has gained increasing attention as it contributes significantly to the global building energy use. The variable refrigerant flow (VRF) system is a common air-conditioning system applied widely in residential and office buildings in China. Understanding the actual operation and performance of VRF systems is fundamental for the energy-efficient design and operation of VRF systems. Previous research on VRF system operation used either limited field data covering certain building types and climate zones or used a questionnaire to obtain a larger dataset. However, they did not capture the wide applications of VRF systems quantitatively across all building types, climate zones, and operating conditions. To fill this gap, statistical and clustering analysis was conducted on the newly proposed key performance indicators of approximately 287,000 VRF systems for residential and commercial buildings in all five climate zones in China. The main findings are: (1) VRF systems are mainly used for cooling in all climate zones in China; (2) among all building types, the duration of use is lowest in residential buildings and highest in hotels and medical buildings; (3) the distribution of the ideal VRF cooling coefficient of performance (COP) is similar across all climate zones and building types; whereas the COPs of ideal VRF heating in the Severe Cold region and Cold regions are lower than those in other climate zones; and (4) partial load operations for VRF systems are common in residential buildings and office buildings due to the part-time-part-space operation mode. These findings can inform the actual application of VRF systems in China, supporting the design, operation, industry standard development, and performance optimization of VRF systems.

Indoor environmental quality and energy use evaluation of a three-star green office building in China with field study

In order to get more comprehensive operation performance on indoor environment quality (IEQ) and energy consumption, a long-time measurement and a field occupants’ satisfaction survey on IEQ performance of the first three-star-operation-certified green office building in Ningbo city of China have been conducted, and environmental energy efficiency (EEE) also has been analyzed. Moreover, IEQ and energy consumption of the green case office building are compared with other green office example buildings of the same climate zone in other literatures. The results show that the actual indoor thermal environment of the green case office building isn’t quite achieving the design goals with the Chinese standard of thermal comfort level II (GB 50736). Although indoor air quality of CO2 concentration and visual environment are consistent with the design goals, the indoor relative humidity doesn’t reach the design goal in most of the year. The questionnaire survey results illustrate that the green case building has a high occupants’ satisfaction on IEQ. The comparison results show that there is no obvious difference in indoor temperature and visual environment between the green case building and the green office example buildings in other studies. The results of occupant’s satisfaction and CO2 concentration of the green case building are better than in other studies. However, the indoor relative humidity of the green case building in every season is much higher than in other researches. Energy use intensity (EUI) of the green case building is about 56.5 kWh/m2·a, which is much lower than the constraint value of the Chinese standard. The actual performance of the green case building is also evaluated by the indicator of EEE. The results of this article can provide useful reference for green building operational performance promotion and feedback for design phase optimization.

Searching for office buildings’ fenestration geometries with a Bi-phase optimization framework

By coupling algorithmic optimization with parametric modeling and performance simulation, the building design process becomes a series of informed decision-making. Algorithmic optimization helps architects find high-performance design choices which balance complicated tradeoffs among various performance objectives. Although algorithmic-optimization aided design is more competent than the traditional manual method, due to complexities in building design, optimization frameworks are not easy to formulate. Focusing on the correlation between energy efficiency, visual comfort, and construction material cost, the current author formulates a bi-phase optimization framework to search for facade fenestration geometries. Afterwards, this optimization framework is applied to one representative office building in China. Optimal design choices are found to have much lower thermal loads and construction cast, but higher visual comfort. This paper highlights how the optimization framework regarding facade fenestration is formulated and how it performs during the building design process.

Study on heating capacity and heat loss of capillary radiant floor heating systems

Radiant floor heating systems with the distinct advantages of low-temperature water supply, energy saving, uniform room temperature and well thermal comfort, are widely used in residential and office buildings in China. And those radiant floors embedded with capillary pipes have been increasing in popularity because of better thermal performance. In this paper, a new simplified calculation for heating capacity, heat loss and surface temperature of radiant heating floor with high-performance insulation layer was provided and validated by measured as well as numerical simulated data. By the simplified calculation method, the influence of each layer material on the heat transfer of capillary radiant heating floor have been analyzed and results show that, (1) the heating capacity will decreased with the increasement of pipe spacing and the descending slop is decided by the ratio of pipe spacing to the equivalent distance from pipes to the room environment; (2) thermal resistance of pipes could be ignored when it is twice more than that of filling material, or it will have negative influence on heating capacity with the increase of pipe spacing.