Search

• Measured vertical air temperature difference distribution with split air-conditioner heating. • Females have lower thermal sensations and skin temperatures than males. • Analyzed predominate local segments under the cold and warm conditions. • Observed different thermal responses to the vertical temperature differences between genders. The effects of vertical temperature differences (VTD) on human thermal comfort have attracted growing attention from researchers when utilizing split air conditioners for winter heating. This study underscores the need to investigate the influences of gender disparities in the context of significant vertical temperature variations, a critical aspect that has not yet been comprehensively explored. Twenty gender-balanced subjects were exposed to a variety of stratified thermal environments created by a split air-conditioner. Their overall and local perceptual and physiological responses were measured at various operative temperatures and VTD. Results show that females have lower thermal sensation vote (TSV) and mean skin temperature under the same environments compared to males. Neutral operative temperatures of females and males are 23.7 ˚C and 20.8 ˚C, respectively. On the cold side, lower leg and foot thermal sensations are dominant whereas chest and back are dominant on the warm side. When females rated "slightly warm" (TSV equaled 1) or "warm" (TSV equaled 2), or males rated "slightly cool" (TSV equaled −1), increased VTD can lower thermal acceptability. The research findings have significant implications for the understanding of gender requirements of stratified heating environments and for maximizing the thermal comfort of the two genders. [ABSTRACT FROM AUTHOR]

• A database covering three different localized airflow systems is built. • Eleven machine learning models are examined for individual thermal sensation prediction. • Air temperature is the major contributor to TSV using global sensitivity analysis. • The C5.0 model has better performance (82.3%) to predict TSV with 8 features. • Outcomes benefit for evaluation and application in buildings to energy savings. Although local air movement acts as a critical factor to enhance human thermal comfort and energy efficiency, the various factors influencing such movement have led to inconsistent publications on how to evaluate and design localised airflow systems in practice. This study aims to identify the main impacting factors for a localised airflow system and predict a cooling performance based on machine learning algorithms. Three typical localised airflow forms, i.e. an isothermal air supply (IASN), non-isothermal air supply (NIASN), and floor fan (FF), were deployed. The experiments were conducted under a variety of temperature/humidity/local air velocity conditions in a well-controlled climate chamber, and a database including 1305 original samples was built. The primary results indicated that a classification tree C5.0 model showed a better prediction performance (83.99%) for a localised airflow system, with 17 input parameters in the model. Through a sensitivity analysis, 8 feature variables were quantified as having significant main effect responses on subjects' thermal sensation votes (TSV), and three environmental factors (temperature, air velocity, and relative humidity) were identified as having the most significant effects. Using the 8 sensitive factors, the C5.0 model was modified with 82.30% accuracy for subject TSV prediction. A tree model demonstrating the decision rules in the C5.0 model was obtained, with air velocity (=0 m/s, >0 m/s) as the first feature variable and root node, and temperature (⩽28°C, >28°C) as the second feature variable and leaf node, respectively. The outcomes that provide the most influential variables and a machine learning model are beneficial for evaluating personal thermal comfort at individual levels and for guiding the application of a localised airflow system in buildings. [ABSTRACT FROM AUTHOR]

This research aims to investigate human thermal responses to air humidity in warm and hot environments and to evaluate the effect of humidity on human thermal comfort. 20 subjects were involved in 12 exposure experiments in a well-controlled climate chamber at three relative humidity levels (40%, 60%, 80%) and four air temperature levels (26 °C, 28 °C, 30 °C, 32 °C) with little indoor airflow. The physical environmental and physiological parameters, as well as subjective questionnaires, were collected simultaneously with the on-going experiments. The results show that in hot environments, particularly when the air temperature exceeds 30 °C, the relative humidity has a significant effect on human thermal responses both physiologically and subjectively. The Standard Effective Temperature (SET) is biased when evaluating human thermal comfort in hot-humid environments without considering human thermal adaptation to humidity. Hence, a humidity correction coefficient e RH is proposed to modify the deviation of the SET under different relative humidity levels, and to quantify the effect of humidity on human acceptable air temperatures. The modified acceptable temperature-humidity zone has been obtained using the modified method. [ABSTRACT FROM AUTHOR]

Human thermal comfort is affected by various interactive variables, revealing the thermal adaptation processes is challenging. Simplifying as a single direct step from triggering factors to assessment, the understanding of interactions and causality among explanatory variables and their link to thermal comfort remains insufficiently explored. An Interaction Matrix-based Path Analysis (IMPA) modeling approach was proposed to examine the direct and indirect effects of variables on thermal comfort and modeling the thermal comfort by combining observed and unobserved factors. To verify the approach, a broader range of variables was investigated in field studies in five climate zones of China. The Back Propagation-Artificial Neural Network (BP-ANN) coding-based interaction matrix described the possible interaction pathways between variables. Based on these interaction pathways and thermal adaptation theory, the results indicated eleven dominant hypotheses with the directed connections. The path analysis modeling method quantified the driving effects and causality between the explanatory variables and thermal sensation under various indoor conditions. It concluded that psychological factors directly affected thermal sensation, while physiological factors displayed an indirect relationship. Environmental and behavioral factors had both direct and indirect effects. Environmental factors contributed the most significant total effects on thermal sensation, followed by psychological and behavioral factors in various environments. The physiological factors had no substantial impact in a neutral environment. The observed variables affecting thermal sensation further underscored the importance of indoor air temperature and thermal expectation. This study could provide new insights into describing the direct and indirect pathways and understanding the thermal adaptation process. [ABSTRACT FROM AUTHOR]

Several conflicting criteria exist in building design optimization, especially energy consumption and indoor environment thermal performance. This paper presents a novel multi-objective optimization model that can assist designers in green building design. The Pareto solution was used to obtain a set of optimal solutions for building design optimization, and uses an improved multi-objective genetic algorithm (NSGA-II) as a theoretical basis for building design multi-objective optimization model. Based on the simulation data on energy consumption and indoor thermal comfort, the study also used a simulation-based improved back-propagation (BP) network which is optimized by a genetic algorithm (GA) to characterize building behavior, and then establishes a GA–BP network model for rapidly predicting the energy consumption and indoor thermal comfort status of residential buildings; Third, the building design multi-objective optimization model was established by using the GA–BP network as a fitness function of the multi-objective Genetic Algorithm (NSGA-II); Finally, a case study is presented with the aid of the multi-objective approach in which dozens of potential designs are revealed for a typical building design in China, with a wide range of trade-offs between thermal comfort and energy consumption. [ABSTRACT FROM AUTHOR]

Designing for indoor thermal environmental conditions is one of the key elements in the energy efficient building design process. This paper introduces a development of the Chinese national Evaluation Standard for indoor thermal environments (Evaluation Standard). International standards including the ASHRAE55, ISO7730, DIN EN, and CIBSE Guide-A have been reviewed and referenced for the development of the Evaluation Standard. In addition, over 28,000 subjects participated in the field study from different climate zones in China and over 500 subjects have been involved in laboratory studies. The research findings reveal that there is a need to update the Chinese thermal comfort standard based on local climates and people's habitats. This paper introduces in detail the requirements for the thermal environment for heated and cooled buildings and free-running buildings in China. [ABSTRACT FROM AUTHOR]

Abstract: IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary. [ABSTRACT FROM AUTHOR]

Abstract: A generic model of Exergy Assessment is proposed for the Environmental Impact of the Building Lifecycle, with a special focus on the natural environment. Three environmental impacts: energy consumption, resource consumption and pollutant discharge have been analyzed with reference to energy-embodied exergy, resource chemical exergy and abatement exergy, respectively. The generic model of Exergy Assessment of the Environmental Impact of the Building Lifecycle thus formulated contains two sub-models, one from the aspect of building energy utilization and the other from building materials use. Combined with theories by ecologists such as Odum, the paper evaluates a building''s environmental sustainability through its exergy footprint and environmental impacts. A case study from Chongqing, China illustrates the application of this method. From the case study, it was found that energy consumption constitutes 70–80% of the total environmental impact during a 50-year building lifecycle, in which the operation phase accounts for 80% of the total environmental impact, the building material production phase 15% and 5% for the other phases. [Copyright &y& Elsevier]

Abstract: According to the Chinese State Council''s “Building Energy Efficiency Management Ordinance”, a large-scale investigation of energy efficiency (EE) in buildings in contemporary China has been carried out in 22 provincial capitals and major cities in China. The aim of this project is to provide reliable information for drawing up the “Decision on reinforcing building energy efficiency” by the Ministry of Construction of China. The surveyed organizations include government departments, research institutions, property developers, design institutions, construction companies, construction consultancy services companies, facility management departments, financial institutions and those which relate to the business of building energy efficiency. In addition, representatives of the media and residents were also involved. A detailed analysis of the results of the investigation concerning aspects of the current situation and trends in building energy consumption, energy efficiency strategy and the implementation of energy efficiency measures has been conducted. The investigation supplies essential information to formulate the market entrance policy for new buildings and the refurbishment policy for existing buildings to encourage the development of energy efficient technology. [Copyright &y& Elsevier]

To study the human local and overall thermal sensations, a series of experiments under various conditions were carried out in a climate control chamber. The adopted analysis method considered the effect of the weight coefficient of local average skin temperature and density of the cold receptors’ distribution in different local body areas. The results demonstrated that the thermal sensation of head, chest, back and hands is warmer than overall thermal sensation. The mean thermal sensation votes of those local areas were more densely distributed. In addition, the thermal sensation of arms, tight and calf was colder than the overall thermal sensation, which pronounced that thermal sensation votes were more dispersed. The thermal sensation of chest and back had a strong linear correlation with overall thermal sensation. Considering the actual scope of air-conditioning regulation, the human body was classified into three local parts: a) head, b) upper part of body and c) lower part of body. The prediction model of both the three-part thermal sensation and overall thermal sensation was developed. Weight coefficients were 0.21, 0.60 and 0.19 respectively. The model provides scientist basis for guiding the sage installation place of the personal ventilation system to achieve efficient energy use. [ABSTRACT FROM AUTHOR]

Seasonal variation of thermal comfort demands directly affects the energy needs for heating or cooling purpose. In previous studies, the differences of neutral temperatures between summer and winter were revealed, but the studies on the difference of human thermal adaption in transitional seasons are insufficient. To clarify this, this paper presents a year-long survey which was carried out in 505 residential buildings in six cities located in the Hot Summer and Cold Winter (HSCW) zone of China involving 11,524 subjects. Results show a significant difference of adaptive responses in different seasons, and a lag of behavioral responses behind climate change in transitional seasons is observed. Occupants not only adjust clothing insulation according to air temperature in different seasons, but also actively control indoor air movement, including closing/opening windows and using fans. The seasonal, monthly and daily neutral temperatures are studied, implying that occupants’ thermal experience has significant effect on their thermal comfort by behavioral, physiological and psychological paths. According to the comparative study, the running mean air temperature method and aPMV model are recommended in free-running space. The findings provide scientific evidence to the concept that dynamic thermal comfort temperature range should be considered in evaluation of indoor thermal environment. [ABSTRACT FROM AUTHOR]

Green building is an inevitable trend in the construction industry which deeply affects the social development of the economy, environment and a series of industries. There is practical significance for the multidimensionally balanced development of green buildings. A model for multi-objective assessment of green building is developed under three dimensions: Objective, Professional and Time (OPT) according to the green building definition. The OPT coordinate system was built up based on the scoring centroid system of both the China Green Building Labelling scheme (GBL) and the Singapore Green Mark (GM) by the introduction of the Coefficient of Variation and Moment of Inertia. Both these frameworks are restructured based on a case study of a practical project in Chongqing which had achieved the highest GBL and GM awards. Results show that GBL distributes its scores more evenly while GM concentrates on energy saving with greater diversity in land supply and building operations (normalized coefficients of variation of 0.435 and 0.350). The project’s compliance coefficients are 1.27 and 0.31 under GBL and GM respectively indicating its higher degree of compliance with the GM framework. The developed model provides multitarget-oriented guidelines for green building design, assessment and standard development. [ABSTRACT FROM AUTHOR]

Highlights: [•] The energy consumption and thermal environment of the two chambers are analyzed. [•] Building envelope insulation will reduce energy consumption in summer. [•] Insulation measures should be considered for walls in directional orientations. [ABSTRACT FROM AUTHOR]

Accurate and real-time assessment of occupant thermal comfort can provide a solid foundation for efficient air conditioning operations. Existing studies already show the feasibility of using contactless technologies for thermal comfort prediction assisted by machine learning algorithms. However, the lack of transparency in machine learning often weakens user trust. This study performs explainable AI analysis to explore the potential of infrared imaging in thermal comfort evaluation. Specifically, an investigation was carried out in a climatic chamber, and infrared cameras were used to collect facial temperature data. Five popular ensemble tree models were employed to construct prediction models, and explainable AI analysis was performed using SHAP (SHapley Additive exPlanations) theory. Results show that combining additional facial information can significantly improve the overall model performance, and certain facial attributes present high contributions based on SHAP values. Combining facial features with explainable AI provides a convincing basis for thermal comfort assessment. The high SHAP values of facial features can also contribute to finding selective occupants with low neutral voting rates, providing evidence for customized cooling or heating from building systems. [ABSTRACT FROM AUTHOR]

• Six original methods to estimate MST were compared in winter conditions. • The errors of the original method were increased in cold conditions. • The variations of local skin temperatures in winter conditions were analyzed. • Four new weighting formulas were proposed with errors reduced up to 77.6%. • A robust method with 4 points of chest, forearm, thigh, calf was recommended. The demands for cooling and heating in buildings were affected by the thermal state of occupants. As an important physiological parameter reflecting thermal state, the mean skin temperature (MST) of human body was generally calculated by using limited sites of local skin temperatures (LSTs) with corresponding weight factors. In a cold climate, the distribution of local skin temperatures (LSTs) might be highly varied due to the thermoregulation mechanism and uneven distribution of clothing insulation. However, the accuracy of the weighting formulas to estimate MST has not been examined in winter conditions by previous studies. In this study, climate chamber experiments were conducted using 20 subjects wearing 9 different winter clothing ensembles exposed for 100 min in three different air temperature 22 °C, 16 °C and 10 °C, respectively. Six original methods to estimate MST were compared to a reference method with 9 local points. Results show the errors of all these methods were increased in cold winter conditions compared to those in neutral winter condition. The variations of LSTs were analyzed and their relationships could be used to modify the weighting formulas. New simplified methods with different weight factors of LST were proposed and validated by using the data from the other two different studies in cold climates. Compared to the original methods, the errors were reduced up to 77.6% by using the new methods. Thus, this study provides reference information for thermal comfort studies about the optimal weighting formulas to estimate MST in winter conditions. [ABSTRACT FROM AUTHOR]

• Climate chamber experiments were conducted to simulate winter commute conditions. • The interactive effects of physical and mental activities on thermal comfort analyzed. • The skin and core temperatures were not significantly affected by mental activities. • Both metabolic rate and mood can affect TSV and TCV by changing heart rate. • Indoor mental status should also be considered when evaluating thermal comfort. The indoor thermal comfort requirements of occupants after winter commutes are subject to variations compared to stable indoor environments. However, the comprehensive effect of mood and physical activities on thermal responses is poorly understood. In this study, 20 sex-balanced participants were recruited to investigate differences in thermal perceptions and physiological responses to thermal environments after winter commutes in a climate chamber. Six different conditions with three different indoor seated activities after step-changing from two different outdoor physical activities were studied. Our findings revealed significant disparities in mood scores among participants engaged in activities such as quiet sitting, office work (typing), and entertainment (watching comedy). The thermal sensation and thermal comfort votes were significantly different between sitting quietly/working and entertainment cases after winter commute by running. Notably, both physical and mental activities exhibited the capacity to impact TSV through alterations in heart rate. This was particularly evident in the context of entertainment activities, where a positive mood was found to mitigate the increase in heart rate, as indicated by wrist pulse measurements, under conditions of elevated metabolic activity. Conversely, no significant differences were observed in skin and core temperatures across different indoor mental activities. This suggests that wrist pulse or heart rate could serve as a valuable additional parameter for enhancing the accuracy of real-time thermal comfort predictions in environments with a constant room temperature. A more satisfying indoor thermal environment could be dynamically created for the well-being of commuters based on the results of this study. [ABSTRACT FROM AUTHOR]

• A single-blinded cross-over study was conducted in 20 urban residences in China. • Efficiencies of HEPA air cleaners at reducing indoor particles were evaluated. • Particle-reduction efficiency was ∼40% over 48 h under normal living conditions. • Particle-reduction efficiency had a significant association with the room volume. • Residences with large rooms should use multiple cleaners to achieve healthy air. Portable air cleaners are commonly used to reduce indoor air particles in China, but few studies have evaluated the treatment efficiency under real living conditions. We aimed to evaluate the efficiency of a portable air cleaner in common residences under normal living conditions. A single-blind cross-over field study was conducted in 20 urban residences in Chongqing, China. In each residence, one portable air cleaner was operated without a high-efficiency particulate air (HEPA) filter (sham filtration) for the first 48 h and with a HEPA filter (true filtration) for the next 48 h in the living room. Concentrations of PM 1.0 , PM 2.5 , respirable suspended particulate matter (RESP), PM 10 , and total suspended particulate matter (TSP) were measured simultaneously in indoor and ambient outdoor air. Compared to sham filtration, the average concentrations of indoor air particles were significantly lower when true filtration was used according to paired-sample t -tests (all p -values <0.05). However, indoor concentrations of PM 2.5 in 16 (80%) residences were still higher than the World Health Organization's (WHO) air quality guideline during true filtration. The removal efficiencies of the portable air cleaners with HEPA filters for these particles were about 40%. The removal efficiencies for PM 1.0 , PM 2.5 , and RESP had significant associations with the room volume, but not with the residence district, season, age of the building, floor level of the apartment, or ambient weather. Our results indicate that a portable air cleaner is effective in improving household air quality, but is not enough to ensure the air quality meeting WHO guideline in all real-world residences in polluted areas. [ABSTRACT FROM AUTHOR]

• The elderly are passive users of air conditioners, and mostly employed natural ventilation. • The thermal sensation of the elderly was insensitive to thermal environment in summer. • The oral temperature, blood pressure and heart rate of the elderly and middle-aged persons were determined to be almost constant when air temperature changed, a different result from that of the young subjects. • The skin temperature could serve as an optimal monitoring parameter for the elderly as a thermal comfort criterion. Elderly demand for indoor thermal comfort and energy conservation is increasing in an aging society. To reveal the thermal responses of the elderly in a warm summer environment, a field study involving experimental measurements was conducted in Chongqing, China. The study included 333 subjects in 17 residential buildings and 119 subjects in 6 elderly nursing homes; it showed that elderly persons as passive users of air conditioners preferred cooling by natural ventilation. The mean thermal sensation vote was insensitive and lower than estimates obtained from the PMV model in warm environments. The physiological responses of eight elderly subjects (65 ± 3) were measured in a climate chamber at 18°C and 34°C and compared with those from eight college students (22 ± 1) and eight middle-aged subjects (50 ± 5). In this chamber, oral temperature, blood pressure, and heart rate of elderly and middle-aged persons were determined to be almost constant as the air temperature was changed to a hot/cold environment for 30 min, a different result from that of the young subjects. However, the skin temperatures for all age groups showed dependency with air temperature conditions, suggesting skin temperature as an optimal monitoring parameter for the entire population. [ABSTRACT FROM AUTHOR]

Highlights • Developed a high-resolution building model using the state-space method. • One-hour time interval overestimates building heating and cooling loads in part-time patterns. • Explored the impact of thermal mass on residential buildings with different compositions and insulation placements. Abstract A high-resolution time interval numerical model is more accurate to analyze the building dynamic thermophysical processes in the intermittent occupancy, while relevant professional software, such as EnergyPlus, is not compatible with different time intervals. The present study aims to investigate the thermal mass effectiveness of external walls on the part-time part-space operation of heating and cooling of a typical residence. A high-resolution model of a typical 3-occupant residential apartment has been developed using the state-space method and validated by the simulation results from EnergyPlus. The model is then amended to calculate building energy demands with fixed heat and cold supply powers from the perspective of system control, in order to interpret the effectiveness of thermal mass with identical recommended U -value in the HSCW (Hot Summer and Cold Winter) zone in terms of room operative temperatures. It is found that high thermal mass does not help to reduce ideal building loads in the residential buildings in the HSCW zone, but it will improve indoor thermal comfort control in real engineering compared to low thermal mass. Regarding thermal insulation placements of heavy weight external walls under the same thermal mass, it is evidenced that the adoption of internal insulation weakens the thermal mass impact of the heavy weight wall composition compared to that of external insulation. It is inferred that the high thermal mass in the composition of external walls should be exposed to the indoor air to avoid overheating in the cooling conditions. [ABSTRACT FROM AUTHOR]

Highlights • New climate zoning method to help improve building energy designs. • Method applicable to diverse climates and will enhance natural resource utilisation. • Method demonstrated in the HSCW zone of China. • Hierarchical Agglomerative Clustering using 166 weather stations (10 years). • New HSCW sub-zones allow improved spatial resolution of heating/cooling loads. Abstract The climate-responsive strategies for energy efficient building design and management require a detailed understanding of the local climatic conditions, while climate zones are fundamental to building regulations and the application of technologies. Smaller and more homogeneous climate zones could help policy-makers and building designers to improve building energy efficiency while improving the indoor thermal environment. A new climate zoning method, with two-tier classification designed for passive building design, is proposed, using climate data (degree-days, relative humidity, solar radiation and wind speed) with Hierarchical Agglomerative Clustering (HAC) following the Ward's method. The method is applied to the Hot Summer and Cold Winter (HSCW) zone of China as a showcase, where there are no fine climate zones for energy efficient building design with diverse climate characteristics. Seven sub-zones that consider both cooling and heating demands are generated in Tier 1. In the second tier, the HSCW zone is further sub-divided into three humidity groups, three solar radiation clusters, and four wind speed clusters. To assess the impact of climate zoning on building heating and cooling, EnergyPlus simulations are conducted with the output of heating and cooling load. The cooling loads decrease from sub-zone A to B to C (mean = 82.8, 65.3, 43.8 kWh m−2, respectively) with sub-zone mean heating A1 larger than A2 and A3, B1 larger than B2, and C1 larger than C2, which is in accordance with the assumption made in the first-tier division. The higher wind speeds can raise the possibility of natural ventilation, and further increase the free-running period (FRP) when heating and cooling are not needed. The proposed zones are mapped and provide a useful reference for the policy/building code makers for heating and cooling strategies in this region. The method to create the climate zones could be applied in any region with local climate data. [ABSTRACT FROM AUTHOR]

Built-up areas tend to comprise a variety of buildings with diverse and complex shapes, functions and construction characteristics. This variety is the source of significant challenges when calculating building energy use at the building stock level. Moreover, the process of developing stock models usually requires large amounts of data that are frequently scarce, nonexistent or at least not publicly available. Under these circumstances, defining a limited set of reference buildings representing the stock is useful to study the actual energy consumption and the potential effects of different energy conservation measures. This paper presents a new method for developing typical residential reference buildings at district level for bottom-up energy modeling purposes. By means of widely and freely available satellite images, an information database of building shapes is created and a clustering analysis of the geometrical features is performed to define a number of archetypes representative of the heating and cooling energy demand of the district. The method is tested and demonstrated through the case study of the Yuzhong District in Chongqing (China) by comparing the Energy Use Intensity (EUI) of the archetypes derived in this way against detailed dynamic simulations. Results show very small differences in the estimated stock energy consumption (+0.03% in heating energy consumption and +2.97% in cooling energy consumption). [ABSTRACT FROM AUTHOR]

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

Abstract: The use of stack may enhance natural ventilation and contaminates migration of buildings. Previous studies have presented some models for quantification of stack effect, however, rarely paid attention to interaction between the shaft and its adjacent space, particularly when there is warmer (or lighter) currents expelled from the adjacent space into the shaft. A quantitative model is developed in this paper for convection of a shaft, both with warm gas expelling from its adjacent space and connected to a cold exterior through top and bottom openings. The model can predict the vertical distributions of temperature and pressure, mass inflow rate, neutral plane location, and is extended to determine the conditions for transition from unidirectional to bi-directional convection. Good agreements are obtained between the predictions of the analytical model and a more sophisticated model, Large Eddy Simulation. To identify the most influential parameters and to quantify their effects on the stack effect, sensitivity studies are conducted with respect to both the shaft configuration parameters (opening area, cross-sectional area and height) and the properties of expelling gas (temperature and mass flow rate). In addition, the critical conditions for transition from unidirectional to bi-directional flow are shown for a hypothetical shaft. [Copyright &y& Elsevier]

[Display omitted] The Hot Summer and Cold Winter (HSCW) climate zone along the Yangtze River Valley Region is an economically well-developed region in China. With the improvement of indoor thermal environments, the Chinese government implemented the control of energy use intensity (EUI) for heating and cooling to prevent the excessive growth of energy usage in the area. There is still a lack of EUI quota-based strategic and technical solutions for new residential buildings that consider both climate characteristics and residents' behaviour. This study set up a EUI quota-based three-step approach that consists of processes of multi-objective optimization, multi-criteria decision-making and integrated solutions analysis. The novel combined approach is implemented in this study that the NSGA-II solves the multi-objective optimization problem and TOPSIS solves the multi-criteria decision-making problem. By applying this novel approach, this study is the first to propose practical, integrated, cost-effective solutions for residential buildings while maintaining a comfortable indoor thermal environment that meets the EUI quota and can be implemented across the region. The proposed optimal integrated solutions are composed of both passive and active measures to improve building thermal performance, to reduce the burden on artificial heating and cooling while improving the performance of air conditioning in extreme weather conditions. This study mapped the full spectrum of solutions and provides rigorous evidence to energy policymakers for forthcoming design standards. [ABSTRACT FROM AUTHOR]

• Temporal and seasonal variations of window opening in residences are explored. • Cross-sectional survey, photography and longitudinal monitoring are combined. • Window operation habits of residents are driven by natural ventilation and fresh air. • Logistic models for window opening are developed and differentiated by seasons. • Outcomes provides evidence for window operation strategies and accurate building simulation. Window operation behavior has been recognized as one of the pivotal factors affecting building energy efficiency and indoor environments. Such behavior could vary from one region to another. A holistic understanding of the temporal and seasonal variations in the operation of residential windows in the Yangtze River region remains insufficiently explored. This paper presents a multi-scale approach by combining cross-sectional surveys, photographic image observations, and longitudinal onsite measurements to investigate the window opening characteristics of residents. The advantage is being able to perform qualitative and quantitative analyses systematically upon the completion of each step. The methodology has been applied to a case study in Chongqing, China. A year-long study revealed the window operation habits of residents in this region who rely greatly on windows for natural ventilation in transient seasons and for fresh air in summer/winter, especially when heating and cooling systems are in operation. Logistic models were developed and differentiated by seasons: transient, winter, summer with natural ventilation, and summer with air conditioning. The models quantified the driving factors and their corresponding variations affecting window opening probabilities in different periods of a year. It can be integrated into building simulations with realistic profiles for more accurate prediction of energy consumption in buildings. The proposed research methodology is applicable to other regions. The gained knowledge of residents' window operation characteristics in this region provides evidence for window operations and building designs/retrofit strategies. [ABSTRACT FROM AUTHOR]

• Develops a holistic large-scale field survey of winter heating in the HSCW zone. • Strong evidence of winter heating patterns classifies as part-time-part-space. • Spatial and temporal elements feature the end-users' heating demand. • Findings support energy policy and design solutions for building heating systems. The increasing demand for improving indoor thermal environment in the hot summer and cold winter climate zone (HSCW) in the Yangtze River region in China poses enormous challenges in terms of energy policy and design solutions for this unique region. A comprehensive understanding of people's habits and behaviors involving winter heating is imperative for decision making for urban heating infrastructure investment strategies that significantly impact the decarbonization of heating. However, there are little studies of a large-scale survey to gain such knowledge acrose the region. The aim of this study is to develop a rigorous survey method in order to obtain reliable data for analysis. Five municipal/capital cities across the upper, middle and downstream Yangtze River were surveyed based on 30 randomly generated locations in each city. A total of 8481 valuable samples were obtained in the survey conducted in the winter from November 2017 to March 2018. It is revealed that air conditioning/air source heat pumps are the predominant systems, accounting for 63% and 58% for bedroom and living room heating respectively. The use patterns of heating are diverse featuring 'part-time-part-space' systems in accordance with the occupancy patterns. There is significant evidence of the habit of opening a window to provide a gap for fresh air irrespective of whether the heating is in use. Two-step cluster analysis is employed to subdivide occupants' heating-related behaviors into three clusters to characterize households. This study fills the knowledge gap of winter-heating-related behaviors. The research outcomes will benefit building energy simulations for energy prediction and help policy makers making decisions on providing strategic guidance in terms of winter heating solutions in this region. [ABSTRACT FROM AUTHOR]

l Predicting heat stress to climate change is needed at individual level. l A method of the Comprehensive Deviation Coefficient (CDC) is proposed. l Subjects' Tsk, Tre and HR to heat exposure are analyzed by multi-dimensional metrics. l Individual differences of physiological responses are quantified via CDC values. l High-risk hot environments and vulnerable individual are identified using CDC method. With increasing global warming, a method to identify individual heat exposure risk and conduct interventions is essential, in order to mitigate impacts of extreme climates on people's health. This paper aims to examine the differences of individual's physiological response in hot environments and consequently proposes a personal-based method to identify potentially vulnerable populations with high risk. A heat exposure experiment was carried out in a climate chamber to build datasets, with nine conditions combining air temperature (35 °C/38 °C/40 °C) and relative humidity (25%/40% /60%). The rectal temperature (Tre), skin temperature (Tsk) and heart rate (HR) of 10 subjects were monitored. Data were analyzed using multiple-dimensional metrics of average deviation(AD), coefficient of variation(CV) and skewness(SKEW). The study introduced the Moment of Inertia (MI) and the Simulated Mass System (MS) in a multidimensional coordinate system and developed a Comprehensive Deviation Coefficient (CDC) method. Using various combinations of AD/CV/SKEW, the values of CDC Tre , CDC Tsk , CDC HR were calculated; the high-risk thermal environment (40 °C/60%) and subject were thus identified. The proposed CDC method enables to distinguish the individual's physiological response differences, under different hot environments and personal characteristics. The equations in this method can be programed in computer and integrated with smart sensor technology, contributing to identify the high-risk environments and provide precautions for susceptible populations, to mitigate the heat exposure hazards on people' health and safety. [ABSTRACT FROM AUTHOR]

• A three-step framework of tracking method are proposed with - data collection, time division and data analysis. • Seasonal time boundaries are identified for energy system feasibility. • Building occupants' thermal comfort and adaptive behavior changed seasonally. • New dynamic comfort temperature zones were formed and modelled. • The new approach could save up to 34.33% in energy use over standard set comfort zones. Occupants' thermal comfort and their adaptation behaviors are essential aspects of building design and energy operation. There is a growing need to better understand the impact of seasonal variation on occupants' dynamic thermal comfort which provides evidence for building energy flexible design and management. The aim of this study is to investigate the interaction between occupants' thermal sensation and adaptive behavior in office buildings. Such understanding can provide detailed adaptation rules of human behavior in dynamic office buildings and quantify energy demands. In this study, a framework of a tracking method is proposed, which combines data collection (continuous monitoring of environmental parameters and daily questionnaire surveys), time boundary division and data analysis. Using the tracking method, field surveys were carried out in three mixed-mode office buildings in Chongqing, China. The time-series data was analyzed based on the indoor operative temperature under free-running conditions and five seasonal periods are classified i.e. Latter Spring (LS), Early Cooling period (EC), Middle Cooling period (MC), Latter Cooling period (LC) and Early Autumn (EA). Results show that for the same outdoor temperatures in different seasons, occupants' clothing insulation varied, indicating that the occupants were more sensitive to environmental changes in EA than in LS, as well as in EC than in LC. The study that flexible energy operation based on the thermal comfort demand can achieve energy savings compared with fixed temperature. [ABSTRACT FROM AUTHOR]